Machines

39 pages, 8448 KiB

Open AccessEditor’s ChoiceArticle

Assessment of a Fully Renewable Generation System with Storage to Cost-Effectively Cover the Electricity Demand of Standalone Grids: The Case of the Canary Archipelago by 2040

by Yago Rivera-Durán, César Berna-Escriche, Yaisel Córdova-Chávez and José Luis Muñoz-Cobo

Machines 2023, 11(1), 101; https://doi.org/10.3390/machines11010101 - 11 Jan 2023

Cited by 12 | Viewed by 2872

Abstract

The change towards a clean electric generation system is essential to achieve the economy decarbonization goal. The Canary Islands Archipelago confronts social, environmental, and economic challenges to overcome the profound change from a fossil fuel-dependent economy to a fully sustainable renewable economy. This [...] Read more.

The change towards a clean electric generation system is essential to achieve the economy decarbonization goal. The Canary Islands Archipelago confronts social, environmental, and economic challenges to overcome the profound change from a fossil fuel-dependent economy to a fully sustainable renewable economy. This document analyzes a scenario with a totally renewable generation system and with total electrification of the economy for the Canary Islands by 2040. In addition, it also shows the significant reduction in this fully renewable system when an optimized interconnection among islands is considered. This scenario consists of a solar PV system of 11 GWp, a wind system of only 0.39 GWp, a pumped storage system of 16.64 GWh (2065 MW), and a lithium-ion battery system of 34.672 GWh (3500 MW), having a system LCOE of 10.1 cEUR/kWh. These results show the certainty of being able to use an autonomous, reliable, and fully renewable system to generate and store the energy needed to dispense with fossil fuels, thus, resulting in a system free of greenhouse gas emissions in the electricity market. In addition, the proposed system has low energy wastage (less than 20%) for a fully renewable, stand-alone, and off-grid system. Full article

(This article belongs to the Special Issue Renewable Energy Power Plants and Systems)

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17 pages, 17150 KiB

Open AccessEditor’s ChoiceArticle

Test and Simulation Study on the Static Load and Pure Longitudinal Slip Characteristics of Non-Pneumatic Tire

by Liangliang Zhu, Ting Xu, Xiaoyu Liu, Mengqi Wu, Xuehan Zhou and Fei Gao

Machines 2023, 11(1), 86; https://doi.org/10.3390/machines11010086 - 10 Jan 2023

Cited by 5 | Viewed by 2196

Abstract

Compared with pneumatic tires, non-pneumatic tires have incomparable performance, in terms of load bearing and safety. In this paper, the static load characteristics and pure longitudinal slip characteristics of the non-pneumatic tire are studied by combining experiments and simulations. The test results show [...] Read more.

Compared with pneumatic tires, non-pneumatic tires have incomparable performance, in terms of load bearing and safety. In this paper, the static load characteristics and pure longitudinal slip characteristics of the non-pneumatic tire are studied by combining experiments and simulations. The test results show that the radial stiffness of the original structure is nonlinear, the pure longitudinal sliding characteristics are seriously inconsistent, the brakes are very sensitive, and the driving is slightly soft. A series of designs have been carried out from the aspects of load-bearing mode and anti-symmetry of the structure, and numerical simulations have been carried out. The results show that the radial secant stiffness of the optimized structure II is increased by 58.8%, and the radial tangent stiffness is increased by 2.96 times, under the premise of ensuring the mass reduction. Additionally, the R square is 0.9932, and the linearity of the radial stiffness curve is greatly improved. The braking and driving conditions under pure longitudinal sliding characteristics are more antisymmetric, which greatly improves the braking sensitivity, but the driving performance is not as good as the original structure. In addition, this paper establishes the evaluation index of the non-pneumatic tire carrying mode, which lays the foundation for further exploration of the non-pneumatic tire carrying mechanism. Full article

(This article belongs to the Section Vehicle Engineering)

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14 pages, 4914 KiB

Open AccessEditor’s ChoiceArticle

Dynamic Modeling and Analysis of Epoxy Gear Considering Material Viscoelasticity

by Hanjie Jia, Jiyong Zhang and Xiangyang Xu

Machines 2023, 11(1), 76; https://doi.org/10.3390/machines11010076 - 8 Jan 2023

Cited by 1 | Viewed by 1391

Abstract

With improvements in lubrication and material strength, the power transmitted by plastic gears has increased significantly. To develop high-performance transmission systems, it is necessary to gain deep insights into the dynamic characteristics of plastic gears. However, because plastics are viscoelastic materials, they do [...] Read more.

With improvements in lubrication and material strength, the power transmitted by plastic gears has increased significantly. To develop high-performance transmission systems, it is necessary to gain deep insights into the dynamic characteristics of plastic gears. However, because plastics are viscoelastic materials, they do not obey Hooke’s law, which is the basis of traditional gear dynamic models. In this study, a refined dynamic model for an epoxy gear pair considering material viscoelasticity and extended tooth contact is established, and the differences in the dynamic responses between an epoxy and a steel gear pair are compared with respect to the dynamic meshing force and dynamic transmission error. The results show that: (1) the plastic gear can restrain the meshing impact, it has a generally lower dynamic meshing force than steel gear pair; (2) the position accuracy is the weak point of plastic gears, and this is significantly affected by the rotation speed; (3) the way to indirectly evaluate the dynamic meshing force by measuring the dynamic transmission error, which is often used for metal gears and is less effective for plastic gears. Full article

(This article belongs to the Section Machine Design and Theory)

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27 pages, 3477 KiB

Open AccessEditor’s ChoiceArticle

An Integrated Application of Motion Sensing and Eye Movement Tracking Techniques in Perceiving User Behaviors in a Large Display Interaction

by Xiaolong Lou, Lili Fu, Xuanbai Song, Mengzhen Ma, Preben Hansen, Yaqin Zhao and Yujie Duan

Machines 2023, 11(1), 73; https://doi.org/10.3390/machines11010073 - 6 Jan 2023

Cited by 1 | Viewed by 1530

Abstract

In public use of a large display, it is a usual phenomenon that multiple users individually participate in respective tasks on a common device. Previous studies have categorized such activity as independent interaction that involves little group engagement. However, by investigating how users [...] Read more.

In public use of a large display, it is a usual phenomenon that multiple users individually participate in respective tasks on a common device. Previous studies have categorized such activity as independent interaction that involves little group engagement. However, by investigating how users approach, participate in, and interact with large displays, we found that parallel use is affected by group factors such as group size and between-user relationship. To gain a thorough understanding of individual and group behaviors, as well as parallel interaction task performance, one 70-inch display-based information searching task and experiment was conducted, in which a mobile eye movement tracking headset and a motion sensing RGB-depth sensor were simultaneously applied. The results showed that (1) a larger group size had a negative influence on the group users’ concentration on the task, perceived usability, and user experience; (2) a close relationship between users contributed to occasional collaborations, which was found to improve the users’ task completion time efficiency and their satisfaction on the large display user experience. This study proves that an integrated application of eye movement tracking and motion sensing is capable of understanding individual and group users’ behaviors simultaneously, and thus is a valid and reliable scheme in monitoring public activities that can be widely used in public large display systems. Full article

(This article belongs to the Special Issue Smart Machines: Applications and Advances in Human Motion Analysis)

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15 pages, 4777 KiB

Open AccessEditor’s ChoiceArticle

Stress and Corrosion Defect Identification in Weak Magnetic Leakage Signals Using Multi-Graph Splitting and Fusion Graph Convolution Networks

by Shaoxuan Zhang, Senxiang Lu and Xu Dong

Machines 2023, 11(1), 70; https://doi.org/10.3390/machines11010070 - 6 Jan 2023

Cited by 2 | Viewed by 1366

Abstract

Weak magnetic flux leak detection is one of the most important non-destructive testing and measurement methods for pipelines. Since different defects cause different damage, it is necessary to classify the different types of defects. Traditional machine learning methods of defect type identification mainly [...] Read more.

Weak magnetic flux leak detection is one of the most important non-destructive testing and measurement methods for pipelines. Since different defects cause different damage, it is necessary to classify the different types of defects. Traditional machine learning methods of defect type identification mainly use feature analysis methods and rely on expert a priori knowledge and the ability of designers. These methods have the following weaknesses: a priori knowledge needs to be designed iteratively, and a priori knowledge design relies on expert experience. In recent years, the rapid development of deep learning methods in the field of machine vision has led to the development of defect analysis in the industry. However, most deep learning methods lack the ability to analyze both detailed information and the overall structure. In this paper, we propose graph convolution networks for splitting and fusing multiple graphs of detail graphs and a root graph. Detail information (detail graphs) provides detailed information for the detection of WMFLs. The structure information (root graph) provides structural information for the detection of WMFLs. This paper uses simulation data and experimental data to verify that the proposed method can identify stress defects and corrosion defects well. The paper explains the experimental results in detail to demonstrate the superiority of the method in industrial methods. Full article

(This article belongs to the Section Machines Testing and Maintenance)

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23 pages, 25897 KiB

Open AccessEditor’s ChoiceArticle

On Constraints and Parasitic Motions of a Tripod Parallel Continuum Manipulator

by Oscar Altuzarra, Luigi Tagliavini, Yuhang Lei, Victor Petuya and Jose Luis Ruiz-Erezuma

Machines 2023, 11(1), 71; https://doi.org/10.3390/machines11010071 - 6 Jan 2023

Cited by 3 | Viewed by 1697

Abstract

A parallel continuum manipulator (PCM) is a mechanism of closed-loop morphology with flexible elements such that their deformation contributes to its mobility. Flexible hexapods are six-degrees-of-freedom (DoF) fully parallel continuum mechanisms already presented in the literature. Devices of reduced mobility, i.e., lower mobility [...] Read more.

A parallel continuum manipulator (PCM) is a mechanism of closed-loop morphology with flexible elements such that their deformation contributes to its mobility. Flexible hexapods are six-degrees-of-freedom (DoF) fully parallel continuum mechanisms already presented in the literature. Devices of reduced mobility, i.e., lower mobility than six DoF, have not been studied so far. An essential characteristic of lower mobility mechanisms is that reduced mobility is due to kinematic constraints generated by mechanical arrangements and passive joints. In rigid-link parallel manipulators, those constraints are expressed as a set of equations relating to the parameters representing the end effector’s pose. As a consequence, independent output pose variables are controllable with the position equations, while dependent output variables undergo parasitic motions. In this paper, the performance of a tripod-type parallel continuum manipulator,

3 P \underset{̲}{F} S

, is compared with the operation of its rigid counterpart

3 \underset{̲}{P} R S

. We will show that in PCMs there are no such geometric constraints expressible with algebraic equations, but it is difficult to perform some types of motion in the end effector with the input torques. Another goal of this paper is to evaluate such limitation of motion in a tripod-like PCM and compare it with the constraints of the rigid

3 \underset{̲}{P} R S

. Finally, the paper shows that there are strong similarities in the reduced mobility of both mechanisms. Full article

(This article belongs to the Section Machine Design and Theory)

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16 pages, 2507 KiB

Open AccessEditor’s ChoiceArticle

Model Predictive Control Method for Autonomous Vehicles in Roundabouts

by Zsófia Farkas, András Mihály and Péter Gáspár

Machines 2023, 11(1), 75; https://doi.org/10.3390/machines11010075 - 6 Jan 2023

Cited by 6 | Viewed by 2521

Abstract

This paper introduces a procedure for controlling autonomous vehicles entering roundabouts. The aim of the centralized controller is to define the velocity profile of each autonomous vehicle by which collisions can be avoided and traveling times can be minimized. To achieve these performances, [...] Read more.

This paper introduces a procedure for controlling autonomous vehicles entering roundabouts. The aim of the centralized controller is to define the velocity profile of each autonomous vehicle by which collisions can be avoided and traveling times can be minimized. To achieve these performances, a model predictive control is introduced based on the solution of an analytical calculation of traveling times spent in the roundabout and designing the autonomous vehicles’ velocity profiles in order to avoid conflict situations while ensuring a time-optimal solution. By the application of the proposed procedure, safety of autonomous vehicles can be enhanced and the possibility of a forming congestion can be minimized. The operation of the proposed method is demonstrated by a few simulation examples in the CarSim simulation environment. Full article

(This article belongs to the Special Issue Current and Future Trends in Control and Automation- Selected Papers from the 30th Mediterranean Conference on Control and Automation (MED ’22))

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20 pages, 6930 KiB

Open AccessEditor’s ChoiceArticle

Multi-Objective Optimization of Magnetorheological Mount Considering Optimal Damping Force and Maximum Adjustable Coefficient

by Jianghua Fu, Chao Huang, Ruizhi Shu, Xing-Quan Li, Ming Chen, Zheming Chen and Bao Chen

Machines 2023, 11(1), 60; https://doi.org/10.3390/machines11010060 - 4 Jan 2023

Viewed by 1444

Abstract

To address the problem of multiple working conditions and complex requirements in magnetorheological fluid (MRF) mounts, a high-precision damping characteristic optimization method is explored. Based on the parallel plate model, the equation of fluid motion in the inertial channel was established according to [...] Read more.

To address the problem of multiple working conditions and complex requirements in magnetorheological fluid (MRF) mounts, a high-precision damping characteristic optimization method is explored. Based on the parallel plate model, the equation of fluid motion in the inertial channel was established according to the Navier–Stokes equation, and the MRF mount damping characteristics were analyzed. Considering the fluid model to be suitable in the steady-state, the model was experimentally verified, and the extended equation was fitted. Multi-objective optimization design was carried out by considering the large damping force and adjustable coefficient as the optimization goal and external geometric dimensions as variables. According to results, under the radial-channel MRF mount structure, the magnet core depth has the least influence on the damping force; furthermore, the damping performance can be quickly improved by changing the height of the inertial channel. The addition of the extended equations further improved the accuracy of the fluid model. The multi-objective optimization design can improve the strength and uniformity of the flux density of the MRF mount damping gap. After optimization, the damping force is increased by 44.64%; moreover, when the current is increased from 1.5 to 1.8 A, the controllable force increases by only 2.26%, and the damping performance is fully exerted. Full article

(This article belongs to the Special Issue Noise and Vibration Control in Dynamic Systems)

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16 pages, 4966 KiB

Open AccessEditor’s ChoiceArticle

A Fault Tolerance Method for Multiple Current Sensor Offset Faults in Grid-Connected Inverters

by Fan Zhang, Guangfeng Jin, Junchao Geng, Tianzhen Wang, Jingang Han, Hubert Razik and Yide Wang

Machines 2023, 11(1), 61; https://doi.org/10.3390/machines11010061 - 4 Jan 2023

Viewed by 1542

Abstract

Three-phase grid-connected inverters have been widely used in the distributed generation system, and the current sensor has been applied in closed-loop control in inverters. When the current sensor offset faults occurs, partial fault features of multiple current sensors disappear from the closed-loop control [...] Read more.

Three-phase grid-connected inverters have been widely used in the distributed generation system, and the current sensor has been applied in closed-loop control in inverters. When the current sensor offset faults occurs, partial fault features of multiple current sensors disappear from the closed-loop control grid-connected system, which leads to difficulties for fault diagnostics and fault-tolerant control. This paper proposes a fault tolerance method based on average current compensation mode to eliminate these adverse effects of fault features. The average current compensation mode compensates the average of the three-phase current to the αβ axis current to realize the fault feature reconstruction of the current sensor. The mode does not affect the normal condition of the system. Then, the data-driven method is used for fault diagnosis, and the corresponding fault tolerant control model is selected according to the diagnosis results. Finally, the experimental results show that the proposed strategy has a good fault tolerance control performance and can improve the fault feature discrimination and diagnostic accuracy. Full article

(This article belongs to the Special Issue Condition Monitoring and Fault Diagnosis of Induction Motors)

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19 pages, 6699 KiB

Open AccessEditor’s ChoiceArticle

Laser Directed Energy Deposition-Based Additive Manufacturing of Fe20Cr5.5AlY from Single Tracks to Bulk Structures: Statistical Analysis, Process Optimization, and Characterization

by Jinoop Arackal Narayanan, Farzaneh Kaji, Mark Zimny and Ehsan Toyserkani

Machines 2023, 11(1), 58; https://doi.org/10.3390/machines11010058 - 4 Jan 2023

Cited by 4 | Viewed by 3644

Abstract

Laser directed energy deposition (LDED) can be deployed for depositing high-performance materials for various engineering applications. Alumina-forming steel is a high-performance material that possesses excellent corrosion and oxidation resistance, finding application in the power generation sector. In the present work, LDED using powder [...] Read more.

Laser directed energy deposition (LDED) can be deployed for depositing high-performance materials for various engineering applications. Alumina-forming steel is a high-performance material that possesses excellent corrosion and oxidation resistance, finding application in the power generation sector. In the present work, LDED using powder feeding (LDED-PF) was used to deposit Fe20Cr5.5AlY alloy using single-track, multi-track, and multi-layer deposition on SS 316L substrate. Response surface methodology (RSM)-based optimization was used to optimize the single-track deposition. The relationship between the track geometry parameters and the build rate with the LDED-PF processing parameters was studied. Further, the nonlinear relationship among the major process parameters was developed and an analysis of variance (ANOVA) was utilized to find significant parameters. The multi-track deposition yielded densely clad layers with a columnar grain structure. The presence of complex oxide slag of Y, Al, and Zr on the clad layer was detected. A micro-hardness of 240–285 HV was observed in the clad layer, with a hardness of 1088–1276 HV at the slag layer. The multi-layered structures showed a relative density of 99.7% with columnar growth and an average microhardness of 242 HV. The study paves the way for the deposition of dense alumina-forming steel structures for building components for power generation applications. Full article

(This article belongs to the Special Issue Additive Manufacturing of Machine Components)

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16 pages, 8610 KiB

Open AccessEditor’s ChoiceArticle

Obstacle Detection by Autonomous Vehicles: An Adaptive Neighborhood Search Radius Clustering Approach

by Wuhua Jiang, Chuanzheng Song, Hai Wang, Ming Yu and Yajie Yan

Machines 2023, 11(1), 54; https://doi.org/10.3390/machines11010054 - 2 Jan 2023

Cited by 4 | Viewed by 2359

Abstract

For autonomous vehicles, obstacle detection results using 3D lidar are in the form of point clouds, and are unevenly distributed in space. Clustering is a common means for point cloud processing; however, improper selection of clustering thresholds can lead to under-segmentation or over-segmentation [...] Read more.

For autonomous vehicles, obstacle detection results using 3D lidar are in the form of point clouds, and are unevenly distributed in space. Clustering is a common means for point cloud processing; however, improper selection of clustering thresholds can lead to under-segmentation or over-segmentation of point clouds, resulting in false detection or missed detection of obstacles. In order to solve these problems, a new obstacle detection method was required. Firstly, we applied a distance-based filter and a ground segmentation algorithm, to pre-process the original 3D point cloud. Secondly, we proposed an adaptive neighborhood search radius clustering algorithm, based on the analysis of the relationship between the clustering radius and point cloud spatial distribution, adopting the point cloud pitch angle and the horizontal angle resolution of the lidar, to determine the clustering threshold. Finally, an autonomous vehicle platform and the offline autonomous driving KITTI dataset were used to conduct multi-scene comparative experiments between the proposed method and a Euclidean clustering method. The multi-scene real vehicle experimental results showed that our method improved clustering accuracy by 6.94%, and the KITTI dataset experimental results showed that the F1 score increased by 0.0629. Full article

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Machines and Applications (IECMA 2022))

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12 pages, 930 KiB

Open AccessEditor’s ChoiceArticle

Characterization of the Anomalous Vibration Response of an Intentionally Mistuned LPT Rotor

by Salvador Rodríguez-Blanco and Carlos Martel

Machines 2023, 11(1), 19; https://doi.org/10.3390/machines11010019 - 24 Dec 2022

Cited by 2 | Viewed by 1343

Abstract

The wind tunnel facility at the Centro de Tecnologías Aeronáuticas was used to perform a set of experiments to study the effect of intentional mistuning on the forced response behavior of an aerodynamically unstable low-pressure turbine rotor. The intentional mistuning patterns were implemented [...] Read more.

The wind tunnel facility at the Centro de Tecnologías Aeronáuticas was used to perform a set of experiments to study the effect of intentional mistuning on the forced response behavior of an aerodynamically unstable low-pressure turbine rotor. The intentional mistuning patterns were implemented by adding a small extra mass to some of the blades. The forced response of the rotor was therefore expected to show two resonance peaks with similar amplitudes, corresponding, respectively, to the vibration frequencies of the blades with and without added mass. However, on the post-processing of the measurements, some anomalous behavior was observed. Near resonance, the system response was synchronous with the forcing, and the frequency sweeps exhibited two resonance peaks, but it was found that the two peaks were clearly different, with the peak at lower frequency showing a much higher vibration amplitude than the high-frequency peak, and with some blades responding at both frequencies with a similar amplitude. In order to give a correct interpretation of the experimental results, a reduced-order model is derived that takes into account only the traveling wave modes coupled by the mistuning. This model, although extremely simple, is capable of reproducing the unexpected behavior of the experiments, and gives a clean explanation of the system response. It is shown that the relative size of the mistuning with respect to the frequency difference of the involved traveling-wave modes is the key parameter for the appearance of this phenomenon. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Turbomachinery)

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23 pages, 6767 KiB

Open AccessEditor’s ChoiceArticle

Advanced Motor Control for Improving the Trajectory Tracking Accuracy of a Low-Cost Mobile Robot

by Luis Mérida-Calvo, Andrés San-Millán Rodríguez, Francisco Ramos and Vicente Feliu-Batlle

Machines 2023, 11(1), 14; https://doi.org/10.3390/machines11010014 - 23 Dec 2022

Cited by 4 | Viewed by 2810

Abstract

Accurate trajectory tracking is a paramount objective when a mobile robot must perform complicated tasks. In high-speed movements, time delays appear when reaching the desired position and orientation, as well as overshoots in the changes of orientation, which prevent the execution of some [...] Read more.

Accurate trajectory tracking is a paramount objective when a mobile robot must perform complicated tasks. In high-speed movements, time delays appear when reaching the desired position and orientation, as well as overshoots in the changes of orientation, which prevent the execution of some tasks. One of the aspects that most influences the tracking performance is the control system of the actuators of the robot wheels. It usually implements PID controllers that, in the case of low-cost robots, do not yield a good tracking performance owing to friction nonlinearity, hardware time delay and saturation. We propose to overcome these problems by designing an advanced process control system composed of a PID controller plus a prefilter combined with a Smith predictor, an anti-windup scheme and a Coulomb friction compensator. The contribution of this article is the motor control scheme and the method to tune the parameters of the controllers. It has been implemented in a well-known low-cost small mobile robot and experiments have been carried out that demonstrate the improvement achieved in the performance by using this control system. Full article

(This article belongs to the Special Issue Advances in Automatic Control)

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16 pages, 4408 KiB

Open AccessEditor’s ChoiceArticle

Identifying Parametric Models Used to Estimate Track Irregularities of a High-Speed Railway

by Sunghoon Choi

Machines 2023, 11(1), 6; https://doi.org/10.3390/machines11010006 - 21 Dec 2022

Cited by 2 | Viewed by 1212

Abstract

This study aims to identify parametric models to estimate track irregularities in high-speed railways with simple acceleration measurements. The primary contribution of current research is the development of effective parametric models with smaller parameters. These parameters are derived from the measured data via [...] Read more.

This study aims to identify parametric models to estimate track irregularities in high-speed railways with simple acceleration measurements. The primary contribution of current research is the development of effective parametric models with smaller parameters. These parameters are derived from the measured data via a specialized track geometry inspection system. An adaptive Kalman filter algorithm, using the displacement estimated from the acceleration signals as the input and measured track irregularities as the output, is applied to obtain the model’s unknown parameters. These models are applied to acceleration measured from high-speed rail vehicles in operation, and track irregularities are estimated in spatial and wavelength domains. The estimated irregularities are compared to the track geometry inspection system’s results. Full article

(This article belongs to the Section Vehicle Engineering)

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17 pages, 3476 KiB

Open AccessEditor’s ChoiceArticle

A General Pose Recognition Method and Its Accuracy Analysis for 6-Axis External Fixation Mechanism Using Image Markers

by Sida Liu, Yimin Song, Binbin Lian and Tao Sun

Machines 2022, 10(12), 1234; https://doi.org/10.3390/machines10121234 - 16 Dec 2022

Viewed by 1688

Abstract

The 6-axis external fixation mechanism with Gough-Stewart configuration has been widely applied to the correction of long bone deformities in orthopedics. Pose recognition of the mechanism is essential for trajectory planning of bone correction, but is usually implemented by the surgeons’ experience, resulting [...] Read more.

The 6-axis external fixation mechanism with Gough-Stewart configuration has been widely applied to the correction of long bone deformities in orthopedics. Pose recognition of the mechanism is essential for trajectory planning of bone correction, but is usually implemented by the surgeons’ experience, resulting in a relatively low level of correction accuracy. This paper proposes a pose recognition method based on novel image markers, and implements accuracy analysis. Firstly, a pose description of the mechanism is established with several freely installed markers, and the layout of the markers is also parametrically described. Then, a pose recognition method is presented by identifying the orientation and position parameters using the markers. The recognition method is general in that it encompasses all possible marker layouts, and the recognition accuracy is investigated by analyzing variations in the marker layout. On this basis, layout principles for markers that achieve a desired recognition accuracy are established, and an error compensation strategy for precision improvement is provided. Finally, experiments were conducted. The results show that volume errors of pose recognition were 0.368 ± 0.130 mm and 0.151 ± 0.045°, and the correction accuracy of the fracture model after taking compensation was 0.214 ± 0.573 mm and −0.031 ± 0.161°, validating the feasibility and accuracy of the proposed methods. Full article

(This article belongs to the Special Issue Development and Applications of Parallel Robots)

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17 pages, 2409 KiB

Open AccessEditor’s ChoiceArticle

Indirect Estimation of Tire Pressure on Several Road Pavements via Interacting Multiple Model Approach

by Renato Brancati and Francesco Tufano

Machines 2022, 10(12), 1221; https://doi.org/10.3390/machines10121221 - 15 Dec 2022

Cited by 3 | Viewed by 1955

Abstract

Generally, tire deflation results in a decrease in both handling performance and tire lifetime, and in fuel consumption increment. Therefore, the real-time knowledge of the pressure is important. Direct approaches via pressure sensors mounted on the rim of each tire are not practical, [...] Read more.

Generally, tire deflation results in a decrease in both handling performance and tire lifetime, and in fuel consumption increment. Therefore, the real-time knowledge of the pressure is important. Direct approaches via pressure sensors mounted on the rim of each tire are not practical, due to technical and economic reasons. Cost-effective solutions with real-time estimation of tire pressure are generally less accurate and reliable than direct ones. Dynamical estimators based on a suspension model need road surface topology information to compute disturbances on the suspension system as an input, which is typically unknown. This paper proposes an innovative approach to estimate tire pressure indirectly, without actual road surface roughness information. A vertical suspension dynamic model is used to build several unscented Kalman filters, parametrised around different road surface topologies. These estimators are combined following the Interacting Multiple Model approach, which gives an acceptable estimation of tire stiffness through a weighted average obtained from a probabilistic model. A known linear static relationship between the tire stiffness and inflation pressure is utilized to indirectly estimate the tire inflation pressure. A Monte Carlo analysis has been performed on a wide range of driving scenarios and vehicle manoeuvres. The results of the estimation have been compared to those of a single unscented Kalman filter, in order to validate the effectiveness of the proposed solution and to highlight the improved performances in monitoring tire pressure. Full article

(This article belongs to the Special Issue Feature Review Papers on Trends and Challenges in Automotive Engineering)

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21 pages, 12924 KiB

Open AccessEditor’s ChoiceArticle

Sliding Mode Based Load Frequency Control and Power Smoothing of Power Systems with Wind and BESS Penetration

by Zhiwen Deng, Chang Xu, Zhihong Huo, Xingxing Han and Feifei Xue

Machines 2022, 10(12), 1225; https://doi.org/10.3390/machines10121225 - 15 Dec 2022

Cited by 7 | Viewed by 1875

Abstract

This study aims to maintain the frequency stability of the power system penetrated by wind power. Hence, a battery energy storage system (BESS) is applied to smooth the wind power output in power systems and to enhance their load frequency control (LFC) capacity. [...] Read more.

This study aims to maintain the frequency stability of the power system penetrated by wind power. Hence, a battery energy storage system (BESS) is applied to smooth the wind power output in power systems and to enhance their load frequency control (LFC) capacity. A novel comprehensive control framework is proposed for power systems integrated with wind farms and BESS based on an adaptive fuzzy super-twisting sliding mode control (AF-SSMC) method. Firstly, the sliding functions and control laws of subsystems are designed according to different relative degrees. Then, the super-twisting algorithm is applied to suppress the chattering of the sliding mode control law. Furthermore, an adaptive fuzzy control method is used to adjust the control gains online for better control performance of the controllers. The Lyapunov stability theory is employed to prove the asymptotic stability of the subsystems. The model of an interconnected thermal power system with wind and BESS penetration is also constructed for simulation analyses. The results indicate that the AF-SSMC method effectively reduces the chattering, and the proposed framework stabilizes the frequency of the power system under system uncertainties and external disturbances. Moreover, the wind farm and BESS combined system accurately tracks a reference power to reduce wind power fluctuations. Full article

(This article belongs to the Special Issue Optimization and Control of Distributed Energy Systems)

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17 pages, 1566 KiB

Open AccessEditor’s ChoiceArticle

View-Invariant Spatiotemporal Attentive Motion Planning and Control Network for Autonomous Vehicles

by Melese Ayalew, Shijie Zhou, Imran Memon, Md Belal Bin Heyat, Faijan Akhtar and Xiaojuan Zhang

Machines 2022, 10(12), 1193; https://doi.org/10.3390/machines10121193 - 9 Dec 2022

Cited by 2 | Viewed by 2024

Abstract

Autonomous driving vehicles (ADVs) are sleeping giant intelligent machines that perceive their environment and make driving decisions. Most existing ADSs are built as hand-engineered perception-planning-control pipelines. However, designing generalized handcrafted rules for autonomous driving in an urban environment is complex. An alternative approach [...] Read more.

Autonomous driving vehicles (ADVs) are sleeping giant intelligent machines that perceive their environment and make driving decisions. Most existing ADSs are built as hand-engineered perception-planning-control pipelines. However, designing generalized handcrafted rules for autonomous driving in an urban environment is complex. An alternative approach is imitation learning (IL) from human driving demonstrations. However, most previous studies on IL for autonomous driving face several critical challenges: (1) poor generalization ability toward the unseen environment due to distribution shift problems such as changes in driving views and weather conditions; (2) lack of interpretability; and (3) mostly trained to learn the single driving task. To address these challenges, we propose a view-invariant spatiotemporal attentive planning and control network for autonomous vehicles. The proposed method first extracts spatiotemporal representations from images of a front and top driving view sequence through attentive Siamese 3DResNet. Then, the maximum mean discrepancy loss (MMD) is employed to minimize spatiotemporal discrepancies between these driving views and produce an invariant spatiotemporal representation, which reduces domain shift due to view change. Finally, the multitasking learning (MTL) method is employed to jointly train trajectory planning and high-level control tasks based on learned representations and previous motions. Results of extensive experimental evaluations on a large autonomous driving dataset with various weather/lighting conditions verified that the proposed method is effective for feasible motion planning and control in autonomous vehicles. Full article

(This article belongs to the Special Issue Dynamics and Control of Autonomous Vehicles)

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18 pages, 6438 KiB

Open AccessEditor’s ChoiceArticle

Wind Turbine Blade Defect Detection Based on Acoustic Features and Small Sample Size

by Yuefan Zhu, Xiaoying Liu, Shen Li, Yanbin Wan and Qiaoqiao Cai

Machines 2022, 10(12), 1184; https://doi.org/10.3390/machines10121184 - 7 Dec 2022

Cited by 5 | Viewed by 2585

Abstract

Wind power has become an important source of electricity for both production and domestic use. However, because wind turbines often operate in harsh environments, they are prone to cracks, blisters, and corrosion of the blade surface. If these defects cannot be repaired in [...] Read more.

Wind power has become an important source of electricity for both production and domestic use. However, because wind turbines often operate in harsh environments, they are prone to cracks, blisters, and corrosion of the blade surface. If these defects cannot be repaired in time, the cracks evolve into larger fractures, which can lead to blade rupture. As such, in this study, we developed a remote non-contact online health monitoring and warning system for wind turbine blades based on acoustic features and artificial neural networks. Collecting a large number of wind turbine blade defect signals was challenging. To address this issue, we designed an acoustic detection method based on a small sample size. We employed the octave to extract defect information, and we used an artificial neural network based on model-agnostic meta-learning (MAML-ANN) for classification. We analyzed the influence of locations and compared the performance of MAML-ANN with that of traditional ANN. The experimental results showed that the accuracy of our method reached 94.1% when each class contained only 50 data; traditional ANN achieved an accuracy of only 85%. With MAML-ANN, the training is fast and the global optimal solution is automatic searched, and it can be expanded to situations with a large sample size. Full article

(This article belongs to the Special Issue Advances in Wind and Solar Energy Generation)

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18 pages, 4198 KiB

Open AccessEditor’s ChoiceArticle

Configuration Design and Optimal Energy Management for Coupled-Split Powertrain Tractor

by Haishi Dou, Hongqian Wei, Youtong Zhang and Qiang Ai

Machines 2022, 10(12), 1175; https://doi.org/10.3390/machines10121175 - 7 Dec 2022

Cited by 5 | Viewed by 1809

Abstract

High-power tractors are regarded as effective operation tools in agriculture, and plugin hybrid tractors have shown potential as agricultural machinery, due to their wide application in energy conservation. However, the allocation of the output power of the motors and engine is a challenging [...] Read more.

High-power tractors are regarded as effective operation tools in agriculture, and plugin hybrid tractors have shown potential as agricultural machinery, due to their wide application in energy conservation. However, the allocation of the output power of the motors and engine is a challenging task, given that the energy management strategy (EMS) is nonlinearly constrained. On the other hand, the structure of the continuous variable transmission (CVT) system is complicated, and affects the price of tractors. In this paper, a variable configuration of a tractor that could have the same performance as a complex CVT system is proposed. To address the EMS issues that have shown poor performance in real time, where the programming runs online, firstly a demand power prediction algorithm is proposed in a rotary tillage operation mode. Secondly, an equivalent fuel consumption minimization strategy (ECMS) is used to optimize the power distribution between the engine and the motors. In addition, the equivalent factor is optimized with an offline genetic algorithm. Thirdly, the equivalent factor is converted into a lookup table, and is used for an online power distribution with different driving mileages and state-of-charge (SOC). The simulation results indicate that the equivalent fuel consumption is reduced by 8.4% and extends the operating mileage of pure electric power. Furthermore, the error between the actual and forecasted demand power is less than 1%. The online EMS could improve the mileage of the tractor working cycle with a more feasible fuel economy based on demand power predictions. Full article

(This article belongs to the Topic Vehicle Dynamics and Control)

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18 pages, 3250 KiB

Open AccessEditor’s ChoiceArticle

Optimization Design of Automotive Body Stiffness Using a Boundary Hybrid Genetic Algorithm

by Haolong Zhong, Ting Xu, Jianglin Yang, Meng Sun and Fei Gao

Machines 2022, 10(12), 1171; https://doi.org/10.3390/machines10121171 - 6 Dec 2022

Cited by 2 | Viewed by 1680

Abstract

At the conceptual design stage, it is critical to use appropriate structural analysis and optimization methods. The thin-walled beam transfer matrix method (TBTMM) is adopted to establish the mathematical model of the simplified vehicle body-in-white (BIW) structure in this paper and compare it [...] Read more.

At the conceptual design stage, it is critical to use appropriate structural analysis and optimization methods. The thin-walled beam transfer matrix method (TBTMM) is adopted to establish the mathematical model of the simplified vehicle body-in-white (BIW) structure in this paper and compare it with the results of the finite element method (S-FEM) to verify the approach. In addition, on the basis of the boundary simulation genetic algorithm (BSGA) and local search procedure, a boundary hybrid genetic algorithm (BHGA) is proposed. BHGA is benchmarked on 20 test functions and is compared with current meta-heuristic algorithms to prove its effectiveness and universality. Finally, considering the bending and torsional stiffness constraints, BIW conceptual model is lightweight and designed with an optimizer. Full article

(This article belongs to the Section Vehicle Engineering)

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24 pages, 12467 KiB

Open AccessEditor’s ChoiceArticle

Stiffness-Performance-Based Redundant Motion Planning of a Hybrid Machining Robot

by Yuhao He, Fugui Xie, Xin-Jun Liu, Zenghui Xie, Huichan Zhao, Yi Yue and Mingwei Li

Machines 2022, 10(12), 1157; https://doi.org/10.3390/machines10121157 - 3 Dec 2022

Cited by 1 | Viewed by 1607

Abstract

Large-scale components usually have complex structures with high local stiffness, and the holes on them are required to be machined with high precision, which makes it important and challenging to study how to efficiently and precisely drill in the large-scale components. This article [...] Read more.

Large-scale components usually have complex structures with high local stiffness, and the holes on them are required to be machined with high precision, which makes it important and challenging to study how to efficiently and precisely drill in the large-scale components. This article presents mobile hybrid machining equipment that consists of a five-axis parallel module, a 2-degree-of-freedom (DoF) robotic, arm and an automated guide vehicle (AGV) connected in series. With the ability of wide-range positioning and precise local processing, it has potential advantages in the drilling processing of large-scale components. Stiffness is one of the most important performances for machining equipment, and it’s highly related to the its configuration. For the discussed equipment, the stiffness is determined by the two-stage-positioning hybrid machining robot, which comprises a five-axis parallel module and a two-DoF robotic arm. The redundant motion of the hybrid machining robot makes it possible to optimize its configuration by reasonably planning redundant motion. Therefore, a redundant motion-planning method based on stiffness performance is proposed. A kinematic analysis of the five-axis parallel module, the robotic arm, and the hybrid machining robot is carried out. A hybrid robot usually consists of several subsystems, and to take the compliance of each subsystem into consideration, the stiffness-modeling method for the hybrid robot with n subsystems connected in series is proposed. The stiffness model of the hybrid machining robot is established by using this method, and the variation of the stiffness magnitude has the same trend as that obtained by using FEA software. Stiffness magnitude and isotropy indices are proposed to evaluate the robot’s stiffness performance along the axis of the spindle and in the plane perpendicular to the axis of the spindle. The redundant motion of the hybrid machining robot is planned by maximizing the stiffness magnitude along the spindle axis, with priority to the stiffness isotropy index. Finally, the drilling experiment is carried out, and the results show that the relative error of the hole diameter obtained under the optimal configuration of the hybrid machining robot is 1.63%, which is smaller than those obtained under the other two configurations for comparison with relative errors of 3.75% and 3.50%, respectively. It proves the validity of the redundant motion-planning method. The proposed stiffness-modeling method and the stiffness-performance indices are also applicable to other hybrid machining robots. Full article

(This article belongs to the Special Issue Development and Applications of Parallel Robots)

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17 pages, 22611 KiB

Open AccessEditor’s ChoiceArticle

A Novel Deep Learning-Based Pose Estimation Method for Robotic Grasping of Axisymmetric Bodies in Industrial Stacked Scenarios

by Yaowei Li, Fei Guo, Miaotian Zhang, Shuangfu Suo, Qi An, Jinlin Li and Yang Wang

Machines 2022, 10(12), 1141; https://doi.org/10.3390/machines10121141 - 1 Dec 2022

Cited by 2 | Viewed by 1416

Abstract

A vision-based intelligent robotic grasping system is essential for realizing unmanned operations in industrial manufacturing, and pose estimation plays an import role in this system. In this study, deep learning was used to obtain the 6D pose of an axisymmetric body which was [...] Read more.

A vision-based intelligent robotic grasping system is essential for realizing unmanned operations in industrial manufacturing, and pose estimation plays an import role in this system. In this study, deep learning was used to obtain the 6D pose of an axisymmetric body which was optimal for robotic grasping in industrial stacked scenarios. We propose a method to obtain the 6D pose of an axisymmetric body by detecting the pre-defined keypoints on the side surface. To realize this method and solve other challenges in industrial stacked scenarios, we propose a multitask real-time convolutional neural network (CNN), named Key-Yolact, which involves object detection, instance segmentation, and multiobject 2D keypoint detection. A small CNN as a decision-making subsystem was designed to score multiple predictions of Key-Yolact, and the body with the highest score is considered the best for grasping. Experiments on a self-built stacked dataset showed that Key-Yolact has a practical tradeoff between inference speed and precision. The inference speed of Key-Yolact is higher by 10 FPS, whereas its precision is decreased by only 7% when compared with the classical multitask Keypoint R-CNN. Robotic grasping experiments showed that the proposed design is effective and can be directly applied to industrial scenarios. Full article

(This article belongs to the Section Automation and Control Systems)

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16 pages, 5214 KiB

Open AccessEditor’s ChoiceArticle

Comparative Analysis of Current and Voltage THD at Different Grid Powers for Powerful Active Front-End Rectifiers with Preprogrammed PWM

by Alexander S. Maklakov, Tao Jing and Alexander A. Nikolaev

Machines 2022, 10(12), 1139; https://doi.org/10.3390/machines10121139 - 1 Dec 2022

Cited by 3 | Viewed by 1666

Abstract

Preprogrammed pulse width modulation (PPWM) techniques are drawing a great deal of interest due to their strong harmonic performance. However, there have not yet been any systematic studies or elaboration of the influence of different grid powers on current and voltage THD using [...] Read more.

Preprogrammed pulse width modulation (PPWM) techniques are drawing a great deal of interest due to their strong harmonic performance. However, there have not yet been any systematic studies or elaboration of the influence of different grid powers on current and voltage THD using PPWM. Therefore, this article focuses on a comparative analysis of current and voltage THD in a system with a three-phase, three-level active front-end (AFE) at different grid powers by applying PPWM. A six-pulse electric drive power circuit and one laboratory measurement platform were designed and set up to achieve the above goals. The comparative results were calculated up to the 50th (THD₅₀) and 100th (THD₁₀₀) harmonics against the frequency of the PPWM, ranging between 150 Hz and 750 Hz. The grid power and AFE power ratio was between 30 and 230 under three different AFE-consumed currents. The experimental results were analyzed and compared, and they demonstrated for the first time how the grid power and AFE power ratio with different PPWM patterns can influence current and voltage THD. The research results suggest that it is necessary to review the existing calculation methods for current and voltage THD using modern electric power quality standards. The results presented in this article also provide a reference point for researchers and engineers when considering the electromagnetic compatibility (EMC) of nonlinear consumers in the design of similar circuits. Full article

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19 pages, 10024 KiB

Open AccessEditor’s ChoiceArticle

Design and Control of a Lower Limb Rehabilitation Robot Based on Human Motion Intention Recognition with Multi-Source Sensor Information

by Pengfei Zhang, Xueshan Gao, Mingda Miao and Peng Zhao

Machines 2022, 10(12), 1125; https://doi.org/10.3390/machines10121125 - 28 Nov 2022

Cited by 2 | Viewed by 2646

Abstract

The research on rehabilitation robots is gradually moving toward combining human intention recognition with control strategies to stimulate user involvement. In order to enhance the interactive performance between the robot and the human body, we propose a machine-learning-based human motion intention recognition algorithm [...] Read more.

The research on rehabilitation robots is gradually moving toward combining human intention recognition with control strategies to stimulate user involvement. In order to enhance the interactive performance between the robot and the human body, we propose a machine-learning-based human motion intention recognition algorithm using sensor information such as force, displacement and wheel speed. The proposed system uses the bi-directional long short-term memory (BILSTM) algorithm to recognize actions such as falling, walking, and turning, of which the accuracy rate has reached 99.61%. In addition, a radial basis function neural network adaptive sliding mode controller (RBFNNASMC) is proposed to track and control the patient’s behavioral intention and the gait of the lower limb exoskeleton and to adjust the weights of the RBF network using the adaptive law. This can achieve a dynamic estimation of the human–robot interaction forces and external disturbances, and it gives the exoskeleton joint motor a suitable driving torque. The stability of the controller is demonstrated using the Lyapunov stability theory. Finally, the experimental results demonstrate that the BILSTM classifier has more accurate recognition than the conventional classifier, and the real-time performance can meet the demand of the control cycle. Meanwhile, the RBFNNASMC controller has a better gait tracking effect compared with the PID controller. Full article

(This article belongs to the Section Automation and Control Systems)

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19 pages, 7410 KiB

Open AccessEditor’s ChoiceArticle

Real-Time NMPC for Speed Planning of Connected Hybrid Electric Vehicles

by Fei Ju, Yuhua Zong, Weichao Zhuang, Qun Wang and Liangmo Wang

Machines 2022, 10(12), 1129; https://doi.org/10.3390/machines10121129 - 28 Nov 2022

Cited by 3 | Viewed by 1318

Abstract

Eco-cruising is considered an effective approach for reducing energy consumption of connected vehicles. Most eco-cruising controllers (ECs) do not comply with real-time implementation requirements when a short sampling interval is required. This paper presents a solution to this problem. Model predictive control (MPC) [...] Read more.

Eco-cruising is considered an effective approach for reducing energy consumption of connected vehicles. Most eco-cruising controllers (ECs) do not comply with real-time implementation requirements when a short sampling interval is required. This paper presents a solution to this problem. Model predictive control (MPC) framework was applied to the speed-planning problem for a power-split hybrid electric vehicle (HEV). To overcome the limitations of time-domain MPC (TMPC), a nonlinear space-domain MPC (SMPC) was proposed in the space domain. A real-time iteration (RTI) algorithm was developed to accelerate nonlinear SMPC computations via generating warm initializations and subsequently forming the SMPC-RTI. Proposed speed controllers were evaluated in a hierarchical EC, where a heuristic energy management strategy was selected for powertrain control. Simulation results indicated that the proposed SMPC yields comparable fuel savings to the TMPC and the globally optimal solution. Meanwhile, SMPC reduced MPC computation time by 41% compared to TMPC, and SMPC-RTI further reduced MPC computation time without compromising optimization. During the hardware-in-loop (HIL) test, the mean computation time was 9.86 ms, demonstrating potential for real-time applications. Full article

(This article belongs to the Special Issue Energy Management and ECO-Driving Strategies of Hybrid Electric Vehicles)

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36 pages, 16046 KiB

Open AccessEditor’s ChoiceReview

Vibration Image Representations for Fault Diagnosis of Rotating Machines: A Review

by Hosameldin Osman Abdallah Ahmed and Asoke Kumar Nandi

Machines 2022, 10(12), 1113; https://doi.org/10.3390/machines10121113 - 23 Nov 2022

Cited by 8 | Viewed by 4071

Abstract

Rotating machine vibration signals typically represent a large collection of responses from various sources in a machine, along with some background noise. This makes it challenging to precisely utilise the collected vibration signals for machine fault diagnosis. Much of the research in this [...] Read more.

Rotating machine vibration signals typically represent a large collection of responses from various sources in a machine, along with some background noise. This makes it challenging to precisely utilise the collected vibration signals for machine fault diagnosis. Much of the research in this area has focused on computing certain features of the original vibration signal in the time domain, frequency domain, and time–frequency domain, which can sufficiently describe the signal in essence. Yet, computing useful features from noisy fault signals, including measurement errors, needs expert prior knowledge and human labour. The past two decades have seen rapid developments in the application of feature-learning or representation-learning techniques that can automatically learn representations of time series vibration datasets to address this problem. These include supervised learning techniques with known data classes and unsupervised learning or clustering techniques with data classes or class boundaries that are not obtainable. More recent developments in the field of computer vision have led to a renewed interest in transforming the 1D time series vibration signal into a 2D image, which can often offer discriminative descriptions of vibration signals. Several forms of features can be learned from the vibration images, including shape, colour, texture, pixel intensity, etc. Given its high performance in fault diagnosis, the image representation of vibration signals is receiving growing attention from researchers. In this paper, we review the works associated with vibration image representation-based fault detection and diagnosis for rotating machines in order to chart the progress in this field. We present the first comprehensive survey of this topic by summarising and categorising existing vibration image representation techniques based on their characteristics and the processing domain of the vibration signal. In addition, we also analyse the application of these techniques in rotating machine fault detection and classification. Finally, we briefly outline future research directions based on the reviewed works. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Fault Diagnosis and Prognosis)

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22 pages, 4490 KiB

Open AccessEditor’s ChoiceReview

Fiber Optic Fiber Bragg Grating Sensing for Monitoring and Testing of Electric Machinery: Current State of the Art and Outlook

by Asep Andi Suryandi, Nur Sarma, Anees Mohammed, Vidyadhar Peesapati and Siniša Djurović

Machines 2022, 10(11), 1103; https://doi.org/10.3390/machines10111103 - 21 Nov 2022

Cited by 13 | Viewed by 2877

Abstract

This paper presents a review of the recent trends and the current state of the art in the application of fiber optic fiber Bragg gratings (FBG) sensing technology to condition the monitoring (CM) and testing of practical electric machinery and the associated power [...] Read more.

This paper presents a review of the recent trends and the current state of the art in the application of fiber optic fiber Bragg gratings (FBG) sensing technology to condition the monitoring (CM) and testing of practical electric machinery and the associated power equipment. FBG technology has received considerable interest in this field in recent years, with research demonstrating that the flexible, multi-physical, and electromagnetic interference (EMI) immune in situ sensing of a multitude of physical measurands of CM interest is possible and cannot be obtained through conventional sensing means. The unique FBG sensing ability has the potential to unlock many of the electric machine CM and design validation restrictions imposed by the limitations of conventional sensing techniques but needs further research to attain wider adoption. This paper first presents the fundamental principles of FBG sensing. This is followed by a description of recent FBG sensing techniques proposed for electric machinery and associated power equipment and a discussion of their individual benefits and limitations. Finally, an outlook for the further application of this technique is presented. The underlying intention is for the review to provide an up-to-date overview of the state of the art in this area and inform future developments in FBG sensing in electric machinery. Full article

(This article belongs to the Special Issue Machine Health Diagnosis & Prognosis by Advanced Sensing and Data Driven Techniques)

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15 pages, 7130 KiB

Open AccessEditor’s ChoiceArticle

In Situ Ultrasonic Testing for Wire Arc Additive Manufacturing Applications

by Ana Beatriz Lopez, José Pedro Sousa, João P. M. Pragana, Ivo M. F. Bragança, Telmo G. Santos and Carlos M. A. Silva

Machines 2022, 10(11), 1069; https://doi.org/10.3390/machines10111069 - 12 Nov 2022

Cited by 4 | Viewed by 2577

Abstract

In this paper, we present a non-destructive testing (NDT) technique based on in situ detection of defects up to 100 °C by ultrasonic testing (UT) during construction of parts by a metal additive manufacturing technology known as wire arc additive manufacturing (WAAM). The [...] Read more.

In this paper, we present a non-destructive testing (NDT) technique based on in situ detection of defects up to 100 °C by ultrasonic testing (UT) during construction of parts by a metal additive manufacturing technology known as wire arc additive manufacturing (WAAM). The proposed technique makes use of interlayer application of commercial solder flux to serve as coupling medium for in situ inspection using a special-purpose UT probe. The experimental work was carried out in deposited ER5356 aluminum straight walls following a threefold structure. First, characterization tests with geometrically similar walls with and without interlayer application of solder flux highlight its neutrality, with no effect on the chemical, metallurgical and mechanical properties of the walls. Secondly, UT tests on walls at temperatures ranging from room temperature to 100 °C demonstrate the satisfactory performance of the solder flux as a coupling medium, with little to no soundwave amplitude losses or noise. Finally, acoustic attenuation, impedance and transmission estimations highlight the effectiveness of the proposed technique, establishing a basis for the future development of automated NDT systems for in situ UT of additive manufacturing processes. Full article

(This article belongs to the Special Issue Design for Additive Manufacturing: Engineering Data and Assessment Tools)

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20 pages, 4347 KiB

Open AccessEditor’s ChoiceArticle

Research on Energy Consumption Generation Method of Fuel Cell Vehicles: Based on Naturalistic Driving Data Mining

by Yangyang Ma, Pengyu Wang, Bin Li and Jianhua Li

Machines 2022, 10(11), 1047; https://doi.org/10.3390/machines10111047 - 9 Nov 2022

Cited by 1 | Viewed by 1483

Abstract

In this paper, an energy consumption generation method is proposed to accurately calculate the energy consumption of fuel cell vehicles (FCVs). A specific driver drives on a route (from Jilin University to FAW Volkswagen) for 331 working days (1 April 2020 to 28 [...] Read more.

In this paper, an energy consumption generation method is proposed to accurately calculate the energy consumption of fuel cell vehicles (FCVs). A specific driver drives on a route (from Jilin University to FAW Volkswagen) for 331 working days (1 April 2020 to 28 July 2021) and collects more than 40,000 s of naturalistic driving data by means of a GPS receiver (FRII-D). To accurately calculate the energy consumption data of FCVs under actual driving cycles, naturalistic driving data mining is first studied. The principal component analysis (PCA) algorithm is used to reduce the dimension of the extracted driving cycle characteristic parameters, the K-means algorithm is used for driving cycle clustering, and the LVQ is used for driving cycle identification. Then, the characteristic parameters correlated to energy consumption are obtained based on the FCV model and regression analysis method. In addition, an energy consumption generation method is designed and proposed based on the characteristic parameters and identification results. Furthermore, the proposed energy consumption generation method can accurately calculate the energy consumption of FCVs, which also provides a reference for further research on the efficient energy management of FCVs. Full article

(This article belongs to the Special Issue Emerging Technologies in New Energy Vehicle)

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17 pages, 5529 KiB

Open AccessEditor’s ChoiceArticle

A GAN-BPNN-Based Surface Roughness Measurement Method for Robotic Grinding

by Guojun Zhang, Changyuan Liu, Kang Min, Hong Liu and Fenglei Ni

Machines 2022, 10(11), 1026; https://doi.org/10.3390/machines10111026 - 4 Nov 2022

Cited by 6 | Viewed by 2049

Abstract

Existing machine vision-based roughness measurement methods cannot accurately measure the roughness of free-form surfaces (with large curvature variations). To overcome this problem, this paper proposes a roughness measurement method based on a generative adversarial network (GAN) and a BP neural network. Firstly, this [...] Read more.

Existing machine vision-based roughness measurement methods cannot accurately measure the roughness of free-form surfaces (with large curvature variations). To overcome this problem, this paper proposes a roughness measurement method based on a generative adversarial network (GAN) and a BP neural network. Firstly, this method takes images and curvature of free-form surfaces as training samples. Then, GAN is trained for roughness measurement through each game between generator and discriminant network by using real samples and pseudosamples (from generator). Finally, the BP neural network maps the image discriminant value of GAN and radius of curvature into roughness value (Ra). Our proposed method automatically learns the features in the image by GAN, omitting the independent feature extraction step, and improves the measurement accuracy by BP neural network. The experiments show that the accuracy of the proposed roughness measurement method can measure free-form surfaces with a minimum roughness of 0.2 μm, and measurement results have a margin of 10%. Full article

(This article belongs to the Special Issue Industrial Process Improvement by Automation and Robotics)

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27 pages, 9687 KiB

Open AccessEditor’s ChoiceArticle

Variable Dimensional Scaling Method: A Novel Method for Path Planning and Inverse Kinematics

by Longfei Jia, Zhiyuan Yu, Haiping Zhou, Zhe Pan, Yangsheng Ou, Yaxing Guo and Yuping Huang

Machines 2022, 10(11), 1030; https://doi.org/10.3390/machines10111030 - 4 Nov 2022

Cited by 4 | Viewed by 1407

Abstract

Traditional methods for solving the inverse kinematics of a hyper-redundant manipulator (HRM) can only plan the path of the end-effector with a complicated solving process, where obstacle avoidance is also not considered. To solve the above problems, a novel method for solving inverse [...] Read more.

Traditional methods for solving the inverse kinematics of a hyper-redundant manipulator (HRM) can only plan the path of the end-effector with a complicated solving process, where obstacle avoidance is also not considered. To solve the above problems, a novel method for solving inverse kinematics of HRM is proposed in this paper: the variable dimension scaling method (VDSM), which can solve complex inverse kinematics while avoiding obstacles. Through this method, the path of the end-effector is scaled under a certain proportion and is adjusted depending on the position of the obstacle, which has good universality. The number of link angles changed is as small as possible in the process of achieving the end-effector moving along the desired path. With the redundancy of HRM, obstacle avoidance can be implemented in any environment by the proposed method. Through simulation and experiments in different environments, the above advantages of VDSM are verified. Full article

(This article belongs to the Special Issue Motion Planning and Advanced Control for Robotics)

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21 pages, 7231 KiB

Open AccessEditor’s ChoiceArticle

Early Fault Warning Method of Wind Turbine Main Transmission System Based on SCADA and CMS Data

by Huanguo Chen, Jie Chen, Juchuan Dai, Hanyu Tao and Xutao Wang

Machines 2022, 10(11), 1018; https://doi.org/10.3390/machines10111018 - 2 Nov 2022

Cited by 3 | Viewed by 1987

Abstract

The main transmission system of wind turbines is a multi-component coupling system, and its operational state is complex and varied. These lead to frequent false alarms and missed alarms in existing monitoring systems. To accurately obtain the operational state of the main transmission [...] Read more.

The main transmission system of wind turbines is a multi-component coupling system, and its operational state is complex and varied. These lead to frequent false alarms and missed alarms in existing monitoring systems. To accurately obtain the operational state of the main transmission system and detect its abnormal operation, an early fault warning method for the main transmission system based on SCADA and CMS data is proposed. Firstly, the SCADA and CMS feature parameters relevant to the operating status of the main transmission system are selected by two different methods separately, and the correlation mechanism between the feature parameters and the operating characteristics of the main transmission system is further analyzed. Secondly, the Long Short-Term Memory (LSTM) network-based prediction model of the main transmission system operating parameters is established, in which SCADA and CMS feature parameters are fused as the input feature vectors. Then, the predicted residuals of the state evaluation parameters are used as the operational state evaluation index. The early fault warning model is established by Analytic Hierarchy Process (AHP) and Kernel Density Estimation (KDE). Finally, a case study is used to verify the correct performance of the proposed method. The results show that this method can realize early warning functions 73 h earlier than the existing SCADA system. The method can provide a theoretical basis for the safe operation and condition-based maintenance of wind turbines. Full article

(This article belongs to the Special Issue Wind Turbine Technologies)

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21 pages, 3965 KiB

Open AccessEditor’s ChoiceArticle

Geometric Error Analysis of a 2UPR-RPU Over-Constrained Parallel Manipulator

by Xu Du, Bin Wang and Junqiang Zheng

Machines 2022, 10(11), 990; https://doi.org/10.3390/machines10110990 (registering DOI) - 29 Oct 2022

Cited by 7 | Viewed by 1433

Abstract

For a 2UPR-RPU over-constrained parallel manipulator, some geometric errors result in internal forces and deformations, which limit the improvement of the pose accuracy of the moving platform and shorten the service life of the manipulator. Analysis of these geometric errors is important for [...] Read more.

For a 2UPR-RPU over-constrained parallel manipulator, some geometric errors result in internal forces and deformations, which limit the improvement of the pose accuracy of the moving platform and shorten the service life of the manipulator. Analysis of these geometric errors is important for restricting them. In this study, an evaluation model is established to analyse the influence of geometric errors on the limbs’ comprehensive deformations for this manipulator. Firstly, the nominal inverse and actual forward kinematics are analysed according to the vector theory and the local product of the exponential formula. Secondly, the evaluation model of the limbs’ comprehensive deformations is established based on kinematics. Thirdly, 41 geometric errors causing internal forces and deformations are identified and the results are verified through simulations based on the evaluation model. Next, two global sensitivity indices are proposed and a sensitivity analysis is conducted using the Monte Carlo method throughout the reachable workspace of the manipulator. The results of the sensitivity analysis indicate that 10 geometric errors have no effects on the average angular comprehensive deformation and that the identified geometric errors have greater effects on the average linear comprehensive deformation. Therefore, the distribution of the global sensitivity index of the average linear comprehensive deformation is more meaningful for accuracy synthesis. Finally, simulations are performed to verify the results of sensitivity analysis. Full article

(This article belongs to the Special Issue New Frontiers in Parallel Robots)

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21 pages, 5085 KiB

Open AccessEditor’s ChoiceArticle

Federated Multi-Model Transfer Learning-Based Fault Diagnosis with Peer-to-Peer Network for Wind Turbine Cluster

by Wanqian Yang and Gang Yu

Machines 2022, 10(11), 972; https://doi.org/10.3390/machines10110972 - 24 Oct 2022

Cited by 5 | Viewed by 1932

Abstract

Intelligent fault diagnosis for a single wind turbine is hindered by the lack of sufficient useful data, while multi-turbines have various faults, resulting in complex distributions. Collaborative intelligence can better solve these problems. Therefore, a peer-to-peer network is constructed with one node corresponding [...] Read more.

Intelligent fault diagnosis for a single wind turbine is hindered by the lack of sufficient useful data, while multi-turbines have various faults, resulting in complex distributions. Collaborative intelligence can better solve these problems. Therefore, a peer-to-peer network is constructed with one node corresponding to one wind turbine in a cluster. Each node is equivalent and functional replicable with a new federated transfer learning method, including model transfer based on multi-task learning and model fusion based on dynamic adaptive weight adjustment. Models with convolutional neural networks are trained locally and transmitted among the nodes. A solution for the processes of data management, information transmission, model transfer and fusion is provided. Experiments are conducted on a fault signal testing bed and bearing dataset of Case Western Reserve University. The results show the excellent performance of the method for fault diagnosis of a gearbox in a wind turbine cluster. Full article

(This article belongs to the Special Issue Machine Learning for Fault Diagnosis of Wind Turbines)

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31 pages, 4118 KiB

Open AccessEditor’s ChoiceReview

Intelligent Mechatronics in the Measurement, Identification, and Control of Water Level Systems: A Review and Experiment

by Paweł Olejnik and Jan Awrejcewicz

Machines 2022, 10(10), 960; https://doi.org/10.3390/machines10100960 - 20 Oct 2022

Cited by 2 | Viewed by 3868

Abstract

In this paper, a unique overview of intelligent machines and mathematical methods designed and developed to measure and to control the water level in industrial or laboratory setups of coupled and cascaded configurations of tanks is made. A systematized and concise overview is [...] Read more.

In this paper, a unique overview of intelligent machines and mathematical methods designed and developed to measure and to control the water level in industrial or laboratory setups of coupled and cascaded configurations of tanks is made. A systematized and concise overview is made of the mechatronic systems used in the measurement, identification, and control of the water level enumerates, the software used in the associated scientific research, modern techniques and sensors, and mathematical models, as well as analysis and control strategies. The broad overview of applications of the last decade is finalized by a proposition of a control system that is based on a parameter estimation of a new experimental setup, an integral dynamic model of the system, a modern mechatronic machine such as the Watson-Marlow peristaltic pump, the Anderson Negele sensor of level, the NI cRIO-9074 controller, and LabVIEW virtual instrumentation. The results of real experimental tests, exploiting a hybrid proportional control, being improved by a numerically predicted water level, are obtained using a few tools, i.e., the static characteristics, the classical step response, and a new pyramid-shaped step function of a discontinuous path-following reference input, being introduced to evaluate the effectiveness and robustness of the regulation of the level height. Full article

(This article belongs to the Special Issue Feature Review Papers on Automation Systems)

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20 pages, 4363 KiB

Open AccessEditor’s ChoiceArticle

Shape Accuracy Improvement in Selective Laser-Melted Ti6Al4V Cylindrical Parts by Sliding Friction Diamond Burnishing

by Gyula Varga, Gergely Dezső and Ferenc Szigeti

Machines 2022, 10(10), 949; https://doi.org/10.3390/machines10100949 - 19 Oct 2022

Cited by 1 | Viewed by 1371

Abstract

Additively manufactured metallic parts usually need postprocessing in order to achieve required shape accuracy. Cylindrical test specimens were produced by selective laser melting from Ti6Al4V powder material with different processing parameters. The aim of postprocessing was modification of shape accuracy. Sliding friction diamond [...] Read more.

Additively manufactured metallic parts usually need postprocessing in order to achieve required shape accuracy. Cylindrical test specimens were produced by selective laser melting from Ti6Al4V powder material with different processing parameters. The aim of postprocessing was modification of shape accuracy. Sliding friction diamond burnishing was applied as the postprocessing method. A five-factor, two-level full factorial design of experiment was implemented with factors being infill laser power, infill laser scan speed, burnishing speed, feed and force. Improvement ratios of two roundness parameters were defined, calculated from experimental data, and studied by main effect and interaction analysis. It has been demonstrated that burnishing feed has the largest main effect to improvement in roundness total and cylindricity. Additionally, parameters of both selective laser melting and diamond burnishing appear in three largest interaction terms. Empirical functions were fit to measurement data. Results show that improvement in roundness parameters are strongly nonlinear functions of all factors. Full article

(This article belongs to the Special Issue Additive Manufacturing of Machine Components)

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16 pages, 3240 KiB

Open AccessEditor’s ChoiceArticle

Teaching Motion Control in Mechatronics Education Using an Open Framework Based on the Elevator Model

by Filippo Sanfilippo, Martin Økter, Tine Eie and Morten Ottestad

Machines 2022, 10(10), 945; https://doi.org/10.3390/machines10100945 - 18 Oct 2022

Cited by 4 | Viewed by 2530

Abstract

Universities and other educational institutions may find it difficult to afford the cost of obtaining cutting-edge teaching resources. This study introduces the adoption of a novel open prototyping framework in the context of mechatronics education, employing low-cost commercial off-the-shelf (COTS) components and tools [...] Read more.

Universities and other educational institutions may find it difficult to afford the cost of obtaining cutting-edge teaching resources. This study introduces the adoption of a novel open prototyping framework in the context of mechatronics education, employing low-cost commercial off-the-shelf (COTS) components and tools for the motion control module. The goal of this study is to propose a novel structure for the motion control module in the engineering mechatronics curriculum. The objective is to foster a new teaching method. From a methodology perspective, students are involved in a series of well-organised theoretical lectures as well as practical, very engaging group projects in the lab. To help students understand, draw connections, and broaden their knowledge, the methods of surface learning and deep learning are frequently mixed thoroughly. The structure of the course as well as the key topics are discussed. The proposed open framework, which consists of an elevator model, is presented in details. Students’ early evaluation indicates that the course organisation and subjects are successful and beneficial. Full article

(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)

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21 pages, 10163 KiB

Open AccessEditor’s ChoiceArticle

Developing and Testing the Proto Type Structure for Micro Tool Fabrication

by Hang Xiao, Xiaolong Hu, Shaoqing Luo and Wei Li

Machines 2022, 10(10), 938; https://doi.org/10.3390/machines10100938 - 16 Oct 2022

Cited by 1 | Viewed by 1520

Abstract

Compared with traditional machine tools, the micro machine tools have advantages of small volume, low cost, less energy consumption, high efficiency and high flexibility. Therefore, it is regarded as an important equipment for micro-cutting machining which has been used widely all over the [...] Read more.

Compared with traditional machine tools, the micro machine tools have advantages of small volume, low cost, less energy consumption, high efficiency and high flexibility. Therefore, it is regarded as an important equipment for micro-cutting machining which has been used widely all over the world and. As a key component of the micro-cutting machine tools, the body structure directly influences the machining performance. Thus, an integral column and base structure for micro machining tools was proposed in this work, and the detailed structural parameters were designed based on parameter analysis. Besides, the static and dynamic performance of the proposed machine were analyzed and compared between the integral structure and the separated one. The deformation and stress of the proposed structures under typical working conditions were studied by numerical simulation, along with the natural frequencies, vibration modes and frequency response peaks. Further, optimization was performed on the integral body structure, the prototype of the micro-machine tool was trial-produced, and the positioning accuracy of each coordinate axis was qualitatively analyzed. In addition, the micro-milling test was carried out with 6061 aluminum alloy to show the performance of the novel cutting machine. The results revealed that the proposed integrated micro-machine bed structure is superior to the separated structure in terms of static deformation and harmonic response characteristics, with good comprehensive mechanical properties, greatly improved static and dynamic performance of the machine tool, significantly improved structural accuracy, improved processing quality of the specimen and good application value. Full article

(This article belongs to the Special Issue High Precision Abrasive Machining: Machines, Processes and Systems)

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25 pages, 6861 KiB

Open AccessEditor’s ChoiceArticle

Morphing Wing Based on Trigonal Bipyramidal Tensegrity Structure and Parallel Mechanism

by Jian Sun, Xiangkun Li, Yundou Xu, Tianyue Pu, Jiantao Yao and Yongsheng Zhao

Machines 2022, 10(10), 930; https://doi.org/10.3390/machines10100930 - 13 Oct 2022

Cited by 2 | Viewed by 2053

Abstract

The development of morphing wings is in the pursuit of lighter weight, higher stiffness and strength, and better flexible morphing ability. A structure that can be used as both the bearing structure and the morphing mechanism is the optimal choice for the morphing [...] Read more.

The development of morphing wings is in the pursuit of lighter weight, higher stiffness and strength, and better flexible morphing ability. A structure that can be used as both the bearing structure and the morphing mechanism is the optimal choice for the morphing wing. A morphing wing composed of a tensegrity structure and a non-overconstrained parallel mechanism was designed. The self-balancing trigonal bipyramidal tensegrity structure was designed based on the shape-finding method and force-equilibrium equation of nodes. The 4SPS-RS parallel mechanism that can complete wing morphing was designed based on the configuration synthesis method. The degree of freedom and inverse solution of the parallel mechanism was obtained based on the screw theory, and the Jacobian matrix of the parallel mechanism was established. The stiffness model of the tensegrity structure and the 4SPS-RS parallel mechanism was established. The relationship between the deformation of the 4SPS-RS parallel mechanism and sweep angle, torsion angle, spanwise bending, and span was obtained. Through the modular assembly and distributed drive, the morphing wing could perform smooth and continuous morphing locally and globally. In the static state, it has the advantages of high stiffness and large bearing capacity. In the process of morphing, it can complete morphing motion with four degrees of freedom in changing sweep, twist, spanwise bending, and span of the wing. Full article

(This article belongs to the Special Issue Development and Applications of Parallel Robots)

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18 pages, 4431 KiB

Open AccessEditor’s ChoiceArticle

A Robust and Efficient UAV Path Planning Approach for Tracking Agile Targets in Complex Environments

by Shunfeng Cui, Yiyang Chen and Xinlin Li

Machines 2022, 10(10), 931; https://doi.org/10.3390/machines10100931 - 13 Oct 2022

Cited by 10 | Viewed by 2023

Abstract

The research into the tracking methods of unmanned aerial vehicles (UAVs) for agile targets is multi-disciplinary, with important application scenarios. Using a quadrotor as an example, in this paper, we mainly researched the tracking-related modeling and application verification of agile targets. We propose [...] Read more.

The research into the tracking methods of unmanned aerial vehicles (UAVs) for agile targets is multi-disciplinary, with important application scenarios. Using a quadrotor as an example, in this paper, we mainly researched the tracking-related modeling and application verification of agile targets. We propose a robust and efficient UAV path planning approach for tracking agile targets aggressively and safely. This approach comprehensively takes into account the historical observations of the tracking target and the surrounding environment of the location. It reliably predicts a short time horizon position of the moving target with respect to the dynamic constraints. Firstly, via leveraging the Bernstein basis polynomial and combining obstacle distribution information around the target, the prediction module evaluated the future movement of the target, presuming that it endeavored to stay away from the obstacles. Then, a target-informed dynamic searching method was embraced as the front end, which heuristically searched for a safe tracking trajectory. Secondly, the back-end optimizer ameliorated it into a spatial–temporal optimal and collision-free trajectory. Finally, the tracking trajectory planner generated smooth, dynamically feasible, and collision-free polynomial trajectories in milliseconds, which is consequently reasonable for online target tracking with a restricted detecting range. Statistical analysis, simulation, and benchmark comparisons show that the proposed method has at least 40% superior accuracy compared to the leading methods in the field and advanced capabilities for tracking agile targets. Full article

(This article belongs to the Special Issue Advanced Data Analytics in Intelligent Industry: Theory and Practice)

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23 pages, 1232 KiB

Open AccessEditor’s ChoiceArticle

Optimal Design of Axial Flux Permanent Magnet Motors for Ship RIM-Driven Thruster

by Hichem Ouldhamrane, Jean-Frédéric Charpentier, Farid Khoucha, Abdelhalim Zaoui, Yahia Achour and Mohamed Benbouzid

Machines 2022, 10(10), 932; https://doi.org/10.3390/machines10100932 - 13 Oct 2022

Cited by 3 | Viewed by 4439

Abstract

This paper deals with the design and optimization of a 2.1 MW rim-driven electric thruster for ship propulsion. For this purpose, a double stator ironless rotor axial flux permanent magnet (AFPM) motor is considered as the propulsion motor. The analytical model of the [...] Read more.

This paper deals with the design and optimization of a 2.1 MW rim-driven electric thruster for ship propulsion. For this purpose, a double stator ironless rotor axial flux permanent magnet (AFPM) motor is considered as the propulsion motor. The analytical model of the selected AFPM motor is presented. The magnetic field in the AFPM machine is calculated using the 3D magnetic charge concept in combination with image theory and permeance functions to take into account the stator slotting effects, and a simple thermal model is used to evaluate the heat dissipation capabilities of the machine and the thermal dependence of the main electromagnetic losses. To optimally design the AFPM, an optimization process based on genetic algorithms is applied to minimize the cost of the active motor materials. An appropriate objective function has been constructed, and different constraints related to the main electrical, geometrical, and mechanical parameters have been taken into account. The achieved results are compared with the performance of a podded radial flux permanent magnet (RFPM) motor, which is considered a reference propulsion motor. The obtained results show a fairly satisfactory improvement in the cost and masses of the active motor materials. Finally, the accuracy of the obtained optimum solution is validated by performing 3D finite element analysis (3D-FEA) simulations. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Electrical Machines and Drives)

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18 pages, 24450 KiB

Open AccessEditor’s ChoiceArticle

Taikobot: A Full-Size and Free-Flying Humanoid Robot for Intravehicular Astronaut Assistance and Spacecraft Housekeeping

by Qi Zhang, Cheng Zhao, Li Fan and Yulin Zhang

Machines 2022, 10(10), 933; https://doi.org/10.3390/machines10100933 - 13 Oct 2022

Cited by 4 | Viewed by 3756

Abstract

This paper proposes a full-size and free-flying humanoid robot named Taikobot that aims to assist astronauts in a space station and maintain spacecrafts between human visits. Taikobot adopts a compact and lightweight (∼25 kg) design to work in microgravity, which also reduces launch [...] Read more.

This paper proposes a full-size and free-flying humanoid robot named Taikobot that aims to assist astronauts in a space station and maintain spacecrafts between human visits. Taikobot adopts a compact and lightweight (∼25 kg) design to work in microgravity, which also reduces launch costs and improves safety during human–robot collaboration. Taikobot’s anthropomorphic dual arm system and zero-g legs allow it to share a set of intravehicular human–machine interfaces. Unlike ground-walking robots, Taikobot maneuvers in a novel push–flight–park (PFP) strategy as an equivalent astronaut in a space station to maximize workspace and flexibility. We propose a PFP motion planning and control method based on centroidal dynamics and multi-contact model. Based on the proposed method, we carried out extensive simulations and verified the feasibility and advantages of the novel locomotion strategy. We also developed a prototype of Taikobot and carried out several ground experiments on typical scenarios where the robot collaborates with human astronauts. The experiments show that Taikobot can do some simple and repetitive tasks along with astronauts and has the potential to help astronauts improve their onboard working efficiency. Full article

(This article belongs to the Topic Intelligent Systems and Robotics)

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13 pages, 1741 KiB

Open AccessEditor’s ChoiceArticle

A Lower Limb Rehabilitation Robot with Rigid-Flexible Characteristics and Multi-Mode Exercises

by Mingjie Dong, Jianping Yuan and Jianfeng Li

Machines 2022, 10(10), 918; https://doi.org/10.3390/machines10100918 - 10 Oct 2022

Cited by 7 | Viewed by 2178

Abstract

Lower limb rehabilitation robot (LLRR) can effectively help restore the lower limb’s motor function of patients with hemiplegia caused by stroke through a large number of targeted and repetitive rehabilitation training. To improve the safety and comfort of robot-assisted lower limb rehabilitation, we [...] Read more.

Lower limb rehabilitation robot (LLRR) can effectively help restore the lower limb’s motor function of patients with hemiplegia caused by stroke through a large number of targeted and repetitive rehabilitation training. To improve the safety and comfort of robot-assisted lower limb rehabilitation, we developed an LLRR with rigid-flexible characteristics; the design of passive joints is used to improve human-machine compatibility; the design of flexible unit makes the mechanism have certain rigid-flexible characteristics. Three different rehabilitation training methods have been developed to adapt to the patients at different stages of rehabilitation, namely, passive exercise, active exercise and resistance exercise, respectively. Experiments with healthy subjects have been conducted to verify the effectiveness of the development of the different training modes of the LLRR, showing good compatibility of the mechanism and good trajectory tracking performance of the developed training methods. Full article

(This article belongs to the Section Automation and Control Systems)

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15 pages, 5561 KiB

Open AccessEditor’s ChoiceArticle

Machining Performance for Ultrasonic-Assisted Magnetic Abrasive Finishing of a Titanium Alloy: A Comparison with Magnetic Abrasive Finishing

by Fujian Ma, Ziguang Wang, Yu Liu, Zhihua Sha and Shengfang Zhang

Machines 2022, 10(10), 902; https://doi.org/10.3390/machines10100902 - 6 Oct 2022

Cited by 5 | Viewed by 1754

Abstract

Titanium alloys are widely used in aerospace, the military industry, electronics, automotive fields, etc., due to their excellent properties such as low density, high strength, high-temperature resistance, and corrosion resistance. Many components need to be finished precisely after being cut in these applications. [...] Read more.

Titanium alloys are widely used in aerospace, the military industry, electronics, automotive fields, etc., due to their excellent properties such as low density, high strength, high-temperature resistance, and corrosion resistance. Many components need to be finished precisely after being cut in these applications. In order to achieve high-quality and high-efficiency finishing of titanium alloys, ultrasonic-assisted magnetic abrasive finishing (UAMAF) was introduced in this research. The machining performance for UAMAF of a titanium alloy was studied by experimentally comparing UAMAF and magnetic abrasive finishing (MAF). The results show that the cutting force of UAMAF can reach 2 to 4 times that of MAF, and it decreases rapidly with the increase in the machining gap due to the energy loss of ultrasonic impact in the transmission between magnetic abrasives. The surface roughness of UAMAF can reach about Ra 0.075 μm, which is reduced by about 59% compared with MAF. The main wear type of the magnetic abrasive is that the diamond grits fell off the magnetic abrasive in both UAMAF and MAF. The uniform wear of the magnetic abrasive is realized, and the utilization ratio of the magnetic abrasive is obviously improved in UAMAF. Full article

(This article belongs to the Special Issue High Precision Abrasive Machining: Machines, Processes and Systems)

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26 pages, 31851 KiB

Open AccessEditor’s ChoiceArticle

Robust Tracking and Clean Background Dense Reconstruction for RGB-D SLAM in a Dynamic Indoor Environment

by Fengbo Zhu, Shunyi Zheng, Xia Huang and Xiqi Wang

Machines 2022, 10(10), 892; https://doi.org/10.3390/machines10100892 - 3 Oct 2022

Viewed by 1505

Abstract

This article proposes a two-stage simultaneous localization and mapping (SLAM) method based on using the red green blue-depth (RGB-D) camera in dynamic environments, which can not only improve tracking robustness and trajectory accuracy but also reconstruct a clean and dense static background model [...] Read more.

This article proposes a two-stage simultaneous localization and mapping (SLAM) method based on using the red green blue-depth (RGB-D) camera in dynamic environments, which can not only improve tracking robustness and trajectory accuracy but also reconstruct a clean and dense static background model in dynamic environments. In the first stage, to accurately exclude the interference of features in the dynamic region from the tracking, the dynamic object mask is extracted by Mask-RCNN and optimized by using the connected component analysis method and a reference frame-based method. Then, the feature points, lines, and planes in the nondynamic object area are used to construct an optimization model to improve the tracking accuracy and robustness. After the tracking is completed, the mask is further optimized by the multiview projection method. In the second stage, to accurately obtain the pending area, which contains the dynamic object area and the newly added area in each frame, a method is proposed, which is based on a ray-casting algorithm and fully uses the result of the first stage. To extract the static region from the pending region, this paper designs divisible and indivisible regions process methods and the bounding box tracking method. Then, the extracted static regions are merged into the map using the truncated signed distance function method. Finally, the clean static background model is obtained. Our methods have been verified on public datasets and real scenes. The results show that the presented methods achieve comparable or better trajectory accuracy and the best robustness, and can construct a clean static background model in a dynamic scene. Full article

(This article belongs to the Special Issue Advances in Mobile Robot Navigation in an Unstructured and Dynamically Cluttered Environment)

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17 pages, 4316 KiB

Open AccessEditor’s ChoiceArticle

Experimental Study on the Influence of Micro-Abrasive and Micro-Jet Impact on the Natural Frequency of Materials under Ultrasonic Cavitation

by Tianjiao Song, Xijing Zhu, Linzheng Ye and Jing Zhao

Machines 2022, 10(10), 891; https://doi.org/10.3390/machines10100891 - 3 Oct 2022

Viewed by 1410

Abstract

The higher the natural frequency of the material is, the more resistant it is to deformation under impulse loading. To explore the influence of micro-abrasive and micro-jet impact on the natural frequency and resonance amplitude value of the material under ultrasonic cavitation, 18 [...] Read more.

The higher the natural frequency of the material is, the more resistant it is to deformation under impulse loading. To explore the influence of micro-abrasive and micro-jet impact on the natural frequency and resonance amplitude value of the material under ultrasonic cavitation, 18 sets of single-factor controlled variable ultrasonic cavitation experiments were carried out on a polished specimen of 6061 aluminum alloy (30 mm × 30 mm × 10 mm). With the increase of the abrasive content in the suspension, the natural frequency of the workpiece first increased, then decreased and remained stable. With the increase of the ultrasonic amplitude, the resonance amplitude value of the material increased, reaching the maximum at 0.1789 m·s⁻² and then decreased. The effect of ultrasonic amplitude on the natural frequency of the material was greater than that of the abrasive content, and the effect of the abrasive content on the common amplitude value was greater than that of the ultrasonic amplitude. This research provides a certain reference significance for exploring the influence of power ultrasonic micro-cutting on material properties and avoiding the occurrence of resonance phenomenon of the workpiece under different working conditions. Full article

(This article belongs to the Section Advanced Manufacturing)

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14 pages, 5271 KiB

Open AccessEditor’s ChoiceArticle

Tool Remaining Useful Life Prediction Method Based on Multi-Sensor Fusion under Variable Working Conditions

by Qingqing Huang, Chunyan Qian, Chao Li, Yan Han, Yan Zhang and Haofei Xie

Machines 2022, 10(10), 884; https://doi.org/10.3390/machines10100884 - 1 Oct 2022

Cited by 1 | Viewed by 1554

Abstract

Under variable working conditions, the tool status signal is affected by changing machine processing parameters, resulting in a decreased prediction accuracy of the remaining useful life (RUL). Aiming at this problem, a method based on multi-sensor fusion for tool RUL prediction was proposed. [...] Read more.

Under variable working conditions, the tool status signal is affected by changing machine processing parameters, resulting in a decreased prediction accuracy of the remaining useful life (RUL). Aiming at this problem, a method based on multi-sensor fusion for tool RUL prediction was proposed. Firstly, the factorization machine (FM) was used to extract the nonlinear processing features in the low-frequency condition signal, and the one-dimensional separable convolution was applied to extract tool life state features from multi-channel high-frequency sensor signals. Secondly, the residual attention mechanism was introduced to weight the low-frequency condition characteristics and high-frequency state characteristics, respectively. Finally, the features extracted in the low-frequency and high-frequency parts were input into the full connection layer to integrate working condition information and state information to suppress the influence of variable conditions and improve prediction accuracy. The experimental results demonstrated that the method could predict the remaining life of the tool effectively, and the accuracy and stability of the model are better than several other methods. Full article

(This article belongs to the Section Advanced Manufacturing)

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20 pages, 2151 KiB

Open AccessEditor’s ChoiceArticle

Dynamic Response in Multiphase Electric Drives: Control Performance and Influencing Factors

by Angel Gonzalez-Prieto, Ignacio González-Prieto, Mario J. Duran and Juan J. Aciego

Machines 2022, 10(10), 866; https://doi.org/10.3390/machines10100866 - 27 Sep 2022

Cited by 5 | Viewed by 1788

Abstract

Speed variable electric drives play a key role in the evolution of electrical mobility. The dynamic performance of these systems is a crucial feature for security purposes. For this reason, a large number of works are focused on identification of the most appropriate [...] Read more.

Speed variable electric drives play a key role in the evolution of electrical mobility. The dynamic performance of these systems is a crucial feature for security purposes. For this reason, a large number of works are focused on identification of the most appropriate control technique to satisfy a transient scenario. In this regard, the dynamic abilities of linear and direct controllers were analysed for three-phase drives. Although some insights about their transient performance were obtained, there are yet some issues to be solved. For instance, speed response was typically omitted, some influencing factors were neglected or the multiphase case was carried out. Considering this information, this work proposes a comparative analysis of the dynamic performance of the most popular regulation strategies for a six-phase electric drive. This study analyses speed, current and voltage responses to achieve an overall view of the system performance. Two concepts were employed to simplify the comprehension of the dynamic behavior of a regulation strategy: reaction time and response capacity. Experimental results are employed to confirm the impact of the different agents on a transient situation. Full article

(This article belongs to the Special Issue Innovative Applications of Multiphase Machines)

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17 pages, 3439 KiB

Open AccessEditor’s ChoiceArticle

Uncertainty Quantification for Full-Flight Data Based Engine Fault Detection with Neural Networks

by Matthias Weiss, Stephan Staudacher, Jürgen Mathes, Duilio Becchio and Christian Keller

Machines 2022, 10(10), 846; https://doi.org/10.3390/machines10100846 - 23 Sep 2022

Cited by 3 | Viewed by 2183

Abstract

Current state-of-the-art engine condition monitoring is based on a minimum of one steady-state data point per flight. Due to the scarcity of available data points, there are difficulties distinguishing between random scatter and an underlying fault introducing a detection latency of several flights. [...] Read more.

Current state-of-the-art engine condition monitoring is based on a minimum of one steady-state data point per flight. Due to the scarcity of available data points, there are difficulties distinguishing between random scatter and an underlying fault introducing a detection latency of several flights. Today’s increased availability of data acquisition hardware in modern aircraft provides continuously sampled in-flight measurements, so-called full-flight data. These full-flight data give access to sufficient data points to detect faults within a single flight, significantly improving the availability and safety of aircraft. Artificial neural networks are considered well suited for the timely analysis of an extensive amount of incoming data. This article proposes uncertainty quantification for artificial neural networks, leading to more reliable and robust fault detection. An existing approach for approximating the aleatoric uncertainty was extended by an Out-of-Distribution Detection in order to take the epistemic uncertainty into account. The method was statistically evaluated, and a grid search was performed to evaluate optimal parameter combinations maximizing the true positive detection rates. All test cases were derived based on in-flight measurements of a commercially operated regional jet. Especially when requiring low false positive detection rates, the true positive detections could be improved 2.8 times while improving response times by approximately 6.9 compared to methods only accounting for the aleatoric uncertainty. Full article

(This article belongs to the Special Issue Diagnostics and Optimization of Gas Turbine)

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