Machines

23 pages, 7868 KiB

Open AccessArticle

An Advanced Diagnostic Approach for Broken Rotor Bar Detection and Classification in DTC Controlled Induction Motors by Leveraging Dynamic SHAP Interaction Feature Selection (DSHAP-IFS) GBDT Methodology

by Muhammad Amir Khan, Bilal Asad, Toomas Vaimann and Ants Kallaste

Machines 2024, 12(7), 495; https://doi.org/10.3390/machines12070495 - 22 Jul 2024

Viewed by 453

Abstract

This paper introduces a sophisticated approach for identifying and categorizing broken rotor bars in direct torque-controlled (DTC) induction motors. DTC is implemented in industrial drive systems as a suitable control method to preserve torque control performance, which sometimes shows its impact on fault-representing [...] Read more.

This paper introduces a sophisticated approach for identifying and categorizing broken rotor bars in direct torque-controlled (DTC) induction motors. DTC is implemented in industrial drive systems as a suitable control method to preserve torque control performance, which sometimes shows its impact on fault-representing frequencies. This is because of the DTC’s closed-loop control nature, whichtriesto reduce speed and torque ripples by changing the voltage profile. The proposed model utilizes the modified Shapley Additive exPlanations (SHAP) technique in combination with gradient-boosting decision trees (GBDT) to detect and classify the abnormalities in BRBs at diverse (0%, 25%, 50%, 75%, and 100%) loading conditions. To prevent overfitting of the proposed model, we used the adaptive fold cross-validation (AF-CV) technique, which can dynamically adjust the number of folds during the optimization process. By employing extensive feature engineering in the original dataset and then applying Shapely Additive exPlanations(SHAP)-based feature selection, our methodology effectively identifies informative features from signals (three-phase current, three-phase voltage, torque, and speed) and motor characteristics. The gradient-boosting decision tree (GBDT) classifier, trained using the given characteristics, extracts consistent and reliable classification performance under different loading circumstances and enables precise and accurate detection and classification of broken rotor bars. The proposed approach (SHAP-Fusion GBDT with AF-CV) is a major advancement in the field of machine learning in detecting motor anomalies at varying loading conditions and proved to be an effective mechanism for preventative maintenance and preventing faults in DTC-controlled induction motors byattaining an accuracy rate of 99% for all loading conditions. Full article

(This article belongs to the Special Issue Machine Learning Based Predictive Maintenance and Condition Monitoring)

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38 pages, 23238 KiB

Open AccessReview

Friction Stir Channeling in Heat Sink Applications: Innovative Manufacturing Approaches and Performance Evaluation

by Sooraj Patel and Amit Arora

Machines 2024, 12(7), 494; https://doi.org/10.3390/machines12070494 - 22 Jul 2024

Viewed by 442

Abstract

The fabrication of compact heat exchangers with precisely designed micro- and mini-channels is crucial for enhancing the efficiency of thermal management systems. Friction stir channeling (FSC) emerges as a cost-effective advanced manufacturing process to create complex integral channels, offering channel shape and size [...] Read more.

The fabrication of compact heat exchangers with precisely designed micro- and mini-channels is crucial for enhancing the efficiency of thermal management systems. Friction stir channeling (FSC) emerges as a cost-effective advanced manufacturing process to create complex integral channels, offering channel shape and size flexibility. This review article highlights the pivotal role of processing parameters in channel formation and maintaining their integrity, necessitating a comprehensive understanding of material flow dynamics. A rigorous assessment has been conducted on the channel under mechanical stresses, including tension, bending, and fatigue. The paper emphasizes the potential of FSC to revolutionize heat sink applications by exploring the fundamental concepts, governing parameters, ongoing enhancements in tool design, microstructural and mechanical properties, and heat transfer performance. Full article

(This article belongs to the Special Issue Advancements in Emerging Additive Manufacturing Techniques for Multifunctional Sustainable Technologies)

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25 pages, 6740 KiB

Open AccessArticle

Design of Active Posture Controller for Trailing-Arm Vehicle: Improving Path-Following and Handling Stability

by Zheng Pan, Boyuan Li, Shiyu Zhou, Shaoxun Liu, Shouyuan Chen and Rongrong Wang

Machines 2024, 12(7), 493; https://doi.org/10.3390/machines12070493 - 22 Jul 2024

Viewed by 355

Abstract

To address the question of which posture trailing-arm vehicles (TAVs) should be adopted while driving, this study introduces an innovative active posture controller (APC) to improve both path-following and handling stability performance. Leveraging a nonlinear tire model that considers corner load variation and [...] Read more.

To address the question of which posture trailing-arm vehicles (TAVs) should be adopted while driving, this study introduces an innovative active posture controller (APC) to improve both path-following and handling stability performance. Leveraging a nonlinear tire model that considers corner load variation and wheel camber, alongside the kinematics and double-track model of TAVs, the impact of vehicle body posture on handling performance has been investigated. To fully utilize the four-wheel independent drive and posture adjustable characteristics of the TAV mechanisms, an integrated nonlinear model predictive control (NMPC) combining APC and tire forces distribution is devised. Through simulations conducted using Simulink-Multibody (2023a), the effectiveness of the proposed controller is demonstrated, particularly when compared to the scheme that does not account for the unique posture adjustment mechanisms of TAVs. Full article

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

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22 pages, 7557 KiB

Open AccessArticle

Fault Diagnosis Method for Tractor Transmission System Based on Improved Convolutional Neural Network–Bidirectional Long Short-Term Memory

by Liyou Xu, Guoxiang Zhao, Sixia Zhao, Yiwei Wu and Xiaoliang Chen

Machines 2024, 12(7), 492; https://doi.org/10.3390/machines12070492 - 21 Jul 2024

Viewed by 448

Abstract

In response to the problems of limited algorithms and low diagnostic accuracy for fault diagnosis in large tractor transmission systems, as well as the high noise levels in tractor working environments, a defect detection approach for tractor transmission systems is proposed using an [...] Read more.

In response to the problems of limited algorithms and low diagnostic accuracy for fault diagnosis in large tractor transmission systems, as well as the high noise levels in tractor working environments, a defect detection approach for tractor transmission systems is proposed using an enhanced convolutional neural network (CNN) and a bidirectional long short-term memory neural network (BILSTM). This approach uses a one-dimensional convolutional neural network (1DCNN) to create three feature extractors of varying scales, directly extracting feature information from different levels of the raw vibration signals. Simultaneously, in order to enhance the model’s predicted accuracy and learn the data features more effectively, it presents the multi-head attention mechanism (MHA). To overcome the issue of high noise levels in tractor working environments and enhance the model’s robustness, an adaptive soft threshold is introduced. Finally, to recognize and classify faults, the fused feature data are fed into a classifier made up of bidirectional long short-term memory (BILSTM) and fully linked layers. The analytical findings demonstrate that the fault recognition accuracy of the method described in this article is over 98%, and it also has better performance in noisy environments. Full article

(This article belongs to the Special Issue Advanced Signal Processing Methods and Deep Neural Networks for Machine Fault Diagnosis)

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18 pages, 10016 KiB

Open AccessArticle

Prediction and Dynamic Simulation Verification of Output Characteristics of Radial Piston Motors Based on Neural Networks

by Chunjin Li, Zhengwen Xia and Yongjie Tang

Machines 2024, 12(7), 491; https://doi.org/10.3390/machines12070491 - 20 Jul 2024

Viewed by 308

Abstract

Radial piston motors are executive components in hydraulic systems, tasked with providing appropriate torque and speed according to load requirements in practical applications. The purpose of this study is to predict the output torque of radial piston hydraulic motors and confirm their suitable [...] Read more.

Radial piston motors are executive components in hydraulic systems, tasked with providing appropriate torque and speed according to load requirements in practical applications. The purpose of this study is to predict the output torque of radial piston hydraulic motors and confirm their suitable operating conditions. Efficiency determination experiments were conducted on physical models, yielding thirty sets of performance data. Torque (output torque) and mechanical efficiency from the experimental data were selected as prediction targets and fitted using two methods: multiple linear regression and neural networks. A dynamic simulation model was built using Adams2020 software to obtain theoretical torque values, enabling the verification of the alignment between the predicted values and simulation results. The results indicate that the error between the theoretical torque of the dynamic model and the physical experiments is 1.9%, with the error of the neural network predictions being within 2%. The dynamic simulation model can yield highly accurate theoretical torque values, providing a reference for the external load of hydraulic motors; additionally, neural networks offer accurate predictions of output torque, thus reducing experimental testing costs. Full article

(This article belongs to the Special Issue Towards Electric Motors and Drives: Condition Monitoring, Performance Prediction and Fault Diagnosis)

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19 pages, 2956 KiB

Open AccessArticle

Industrial Robot Trajectory Optimization Based on Improved Sparrow Search Algorithm

by Fei Ma, Weiwei Sun, Zhouxiang Jiang, Shuangfu Suo, Xiao Wang and Yue Liu

Machines 2024, 12(7), 490; https://doi.org/10.3390/machines12070490 - 20 Jul 2024

Viewed by 343

Abstract

This paper proposes an enhanced multi-strategy sparrow search algorithm to optimize the trajectory of a six-axis industrial robot, addressing issues of low efficiency and high vibration impact on joints during operation. Initially, the improved D-H parametric method is employed to establish both forward [...] Read more.

This paper proposes an enhanced multi-strategy sparrow search algorithm to optimize the trajectory of a six-axis industrial robot, addressing issues of low efficiency and high vibration impact on joints during operation. Initially, the improved D-H parametric method is employed to establish both forward and inverse kinematic models of the robot. Subsequently, a 3-5-3 mixed polynomial interpolation trajectory planning approach is applied to the robot. Building upon the conventional sparrow algorithm, a two-dimensional Logistic chaotic system initializes the population. Additionally, a Levy flight strategy and nonlinear adaptive weighting are introduced to refine the discoverer position update operator, while an inverse learning strategy enhances the vigilante position update operator. These modifications boost both the local and global search capabilities of the algorithm. The improved sparrow algorithm, based on 3-5-3 hybrid polynomial trajectory planning, is then used for the time-optimal trajectory planning of the robot. This is compared with traditional sparrow search algorithm and particle swarm algorithm optimization results. The findings indicate that the proposed enhanced sparrow search algorithm outperforms both the standard sparrow algorithm and the particle swarm algorithm in terms of convergence speed and accuracy for robot trajectory optimization. This can lead to the increased work efficiency and performance of the robot. Full article

(This article belongs to the Special Issue Industry 4.0: Intelligent Robots in Smart Manufacturing)

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19 pages, 17427 KiB

Open AccessArticle

Damage Mechanism Analysis of the Connecting Screw of Turbine Disk-Drum Assembly

by Haijun Wang, Shengxu Wang, Pu Xue, Yongxin Guo and Liang Jiang

Machines 2024, 12(7), 489; https://doi.org/10.3390/machines12070489 - 19 Jul 2024

Viewed by 241

Abstract

The turbine disk-drum is one of the key components of an aero-engine and its assembly is connected with high-strength refined screws. But due to the uncoordinated rotation and deformation, the screws have abnormal wear damage. Through detailed contact stress analysis of screw body [...] Read more.

The turbine disk-drum is one of the key components of an aero-engine and its assembly is connected with high-strength refined screws. But due to the uncoordinated rotation and deformation, the screws have abnormal wear damage. Through detailed contact stress analysis of screw body and component level using the finite element method, combined with experimental observation, the mechanism of wear damage of screw surface in screws is determined. It mainly includes the following: Firstly, the finite element method is used to calculate the deformation and stress distribution of the connecting screw of the turbine disk-drum assembly. Then, after the overspeed test, the morphology of the screws disassembled from the disk-drum assembly is evaluated. It was found that the wear degree in the circumferential direction and axial direction of the screw was quite different, that is, the screw wear experiment was consistent with the finite element analysis results. Finally, the influence of different rotation states and screw tightening states on screw wear was compared and analyzed. Conclusions obtained in this paper will be helpful to improve the assembly reliability of turbine drum. Full article

(This article belongs to the Special Issue Advances in Intelligent Fault Diagnosis of Rotating Machinery)

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21 pages, 9169 KiB

Open AccessArticle

Topology Analysis and Structural Optimization of Air Suspension Mechanical-Vibration-Reduction Wheels

by Xiao Meng, Xianying Feng, Peihua Liu and Xinhua Sun

Machines 2024, 12(7), 488; https://doi.org/10.3390/machines12070488 - 19 Jul 2024

Viewed by 361

Abstract

This paper designs a kind of air suspension mechanical-vibration-reduction wheel for mining engineering vehicles; the research work on topology analysis and the structural optimization of the inner and outer rims are carried out with this wheel as the research object. Using Workbench finite-element [...] Read more.

This paper designs a kind of air suspension mechanical-vibration-reduction wheel for mining engineering vehicles; the research work on topology analysis and the structural optimization of the inner and outer rims are carried out with this wheel as the research object. Using Workbench finite-element analysis software, taking the results of static analysis and modal analysis of the two as constraints, a variety of structural improvement styles are obtained through a topology analysis method and compared and verified, and a more reasonable improvement result is selected and assembled into a whole wheel for final analysis and verification. The results show that the optimization results of the wheel still meet the design’s load-bearing requirements, and the weight is lighter; the topology analysis results are ideal. Full article

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

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19 pages, 13096 KiB

Open AccessArticle

Investigation of the Electrical Impedance Signal Behavior in Rolling Element Bearings as a New Approach for Damage Detection

by Florian Michael Becker-Dombrowsky, Johanna Schink, Julian Frischmuth and Eckhard Kirchner

Machines 2024, 12(7), 487; https://doi.org/10.3390/machines12070487 - 19 Jul 2024

Viewed by 526

Abstract

The opportunities of impedance-based condition monitoring for rolling bearings have been shown earlier by the authors: Changes in the impedance signal and the derived features enable the detection of pitting damages. Localizing and measuring the pitting length in the raceway direction is possible. [...] Read more.

The opportunities of impedance-based condition monitoring for rolling bearings have been shown earlier by the authors: Changes in the impedance signal and the derived features enable the detection of pitting damages. Localizing and measuring the pitting length in the raceway direction is possible. Furthermore, the changes in features behavior are physically explainable. These investigations were focused on a single bearing type and only one load condition. Different bearing types and load angles were not considered yet. Thus, the impedance signals and their features of different bearing types under different load angles are investigated and compared. The signals are generated in fatigue tests on a rolling bearing test rig with conventional integrated vibration analysis based on structural borne sound. The rolling bearing impedance is gauged using an alternating current measurement bridge. Significant changes in the vibration signals mark the end of the fatigue tests. Therefore, comparing the response time of the impedance can be compared to the vibration signal response time. It can be shown that the rolling bearing impedance is an instrument for condition monitoring, independently from the bearing type. In case of pure radial loads, explicit changes in the impedance signal are detectable, which indicate a pitting damage. Under combined loads, the signal changes are detectable as well, but not as significant as under radial load. Damage-indicating signal changes occur later compared to pure radial loads, but nevertheless enable an early detection. Therefore, the rolling bearing impedance is an instrument for pitting damage detection, independently from bearing type and load angle. Full article

(This article belongs to the Special Issue Intelligent Machinery Fault Diagnosis and Maintenance)

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13 pages, 1723 KiB

Open AccessArticle

The Coupled Wing Morphing of Ornithopters Improves Attitude Control and Agile Flight

by Yu Cai, Guangfa Su, Jiannan Zhao and Shuang Feng

Machines 2024, 12(7), 486; https://doi.org/10.3390/machines12070486 - 19 Jul 2024

Viewed by 351

Abstract

Bird wings are exquisite mechanisms integrated with multiple morphological deformation joints. The larger avian species are particularly adept at utilizing their wings’ flapping, folding, and twisting motions to control the wing angle and area. These motions mainly involve different types of spanwise folding [...] Read more.

Bird wings are exquisite mechanisms integrated with multiple morphological deformation joints. The larger avian species are particularly adept at utilizing their wings’ flapping, folding, and twisting motions to control the wing angle and area. These motions mainly involve different types of spanwise folding and chordwise twisting. It is wondered whether the agile maneuverability of birds is based on the complex coupling of these wing morphing changes. To investigate this issue, we designed a two-section wing structure ornithopter capable of simultaneously controlling both spanwise folding and chordwise twisting and applied it to research on heading control. The experimental data collected from outdoor flights describe the differing flight capabilities between the conventional and two-section active twist wing states, indicating that incorporating an active twist structure enhances the agility and maneuverability of this novel flapping aircraft. In the experiments on yaw control, we observed some peculiar phenomena: although the twisting motion of the active twist ornithopter wings resembles that of a fixed-wing aileron control, due to the intricate coupling of the wing flapping and folding, the ornithopter, under the control of active twist structures, exhibited a yaw direction opposite to the expected direction (directly applying the logic assumed by the fixed-wing aileron control). Addressing this specific phenomenon, we provide a plausible model explanation. In summary, our study with active twist mechanisms on ornithopters corroborates the positive impact of active deformation on their attitude agility, which is beneficial for the design of similar bio-inspired aircraft in the future. Full article

(This article belongs to the Special Issue Advances and Applications in Unmanned Aerial Vehicles)

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22 pages, 1068 KiB

Open AccessArticle

Integrated Control of a Wheel–Track Hybrid Vehicle Based on Adaptive Model Predictive Control

by Boyuan Li, Zheng Pan, Junhua Liu, Shiyu Zhou, Shaoxun Liu, Shouyuan Chen and Rongrong Wang

Machines 2024, 12(7), 485; https://doi.org/10.3390/machines12070485 - 19 Jul 2024

Viewed by 372

Abstract

Hybrid wheel–track systems have found extensive applications due to the advantages a combination of wheels and tracks. However, the coupling influence between the wheeled and tracked mechanisms poses a challenge to stable and efficient controller design and implementation. This paper focuses on the [...] Read more.

Hybrid wheel–track systems have found extensive applications due to the advantages a combination of wheels and tracks. However, the coupling influence between the wheeled and tracked mechanisms poses a challenge to stable and efficient controller design and implementation. This paper focuses on the lateral dynamic control of a vehicle in scenarios where both tracks and wheels are in contact with the ground. A dynamic model of a vehicle is first established based on the tire brush model and linearized general track model. Based on the dynamic model, a novel adaptive model predictive control (AMPC) method is designed considering the coupling and nonlinearity of the wheels and tracks to simultaneously regulate both mechanisms. Compared with traditional model predictive control approaches, the AMPC controller takes the side-slip angle and slip ratio as constraints to prevent the vehicle from reaching unstable states. Simulations are conducted to validate the effectiveness of the controller, and the results indicate that the controller has the capacity to optimize the objective’s yaw-rate response while maintaining lateral vehicle stability and preventing slip by imposing constraints. Full article

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

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33 pages, 6608 KiB

Open AccessReview

A Review of the Intelligent Condition Monitoring of Rolling Element Bearings

by Vigneshwar Kannan, Tieling Zhang and Huaizhong Li

Machines 2024, 12(7), 484; https://doi.org/10.3390/machines12070484 - 18 Jul 2024

Viewed by 423

Abstract

Bearing component damage contributes significantly to rotating machinery failures. It is vital for the rotor-bearing system to be in good condition to ensure the proper functioning of the machine. Over recent decades, extensive research has been devoted to the condition monitoring of rotational [...] Read more.

Bearing component damage contributes significantly to rotating machinery failures. It is vital for the rotor-bearing system to be in good condition to ensure the proper functioning of the machine. Over recent decades, extensive research has been devoted to the condition monitoring of rotational machinery, with a particular focus on bearing health. This paper provides a comprehensive literature review of recent advancements in intelligent condition monitoring technologies for rolling element bearings. Fundamental monitoring strategies are introduced, covering various sensing, signal processing, and feature extraction techniques for detecting defects in rolling element bearings. While vibration-based monitoring remains prevalent, alternative sensor types are also explored, offering complementary diagnostic capabilities or detecting different defect types compared to accelerometers alone. Signal processing and feature extraction techniques, including time domain, frequency domain, and time–frequency domain analysis, are discussed for their ability to provide diverse perspectives for signal representation, revealing unique insights relevant to condition monitoring. Special attention is given to information fusion methodologies and the application of intelligent algorithms. Multisensor systems, whether homogeneous or heterogeneous, integrated with information fusion techniques hold promise in enhancing accuracy and reliability by overcoming limitations associated with single-sensor monitoring. Furthermore, the adoption of AI techniques, such as machine learning, metaheuristic optimisation, and deep-learning methods, has led to significant advancements in condition monitoring, yielding successful outcomes with improved accuracy and robustness in various studies. Finally, avenues for further advancements to improve monitoring accuracy and reliability are identified, offering insights into future research directions. Full article

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

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26 pages, 6952 KiB

Open AccessArticle

Maintainability Assessment during the Design Phase: Integrating MTA and UNE 151001

by Franco Donaire, Orlando Durán, José Ignacio Vergara and Adolfo Arata

Machines 2024, 12(7), 483; https://doi.org/10.3390/machines12070483 - 17 Jul 2024

Viewed by 343

Abstract

The focus on maintenance actions in the early design phases has been a trend in recent years. The main sources of information during the design of the maintainability process include operator reports, maintainer experience, failure history, and manufacturer recommendations. During this process, an [...] Read more.

The focus on maintenance actions in the early design phases has been a trend in recent years. The main sources of information during the design of the maintainability process include operator reports, maintainer experience, failure history, and manufacturer recommendations. During this process, an important aspect is related to the configuration of maintenance tasks and interventions, such as their main phases, activities, and durations. The allocation or estimation of maintainability involves identifying and/or estimating the mean time to repair (MTTR) for each component or system. The time of the maintenance tasks or the repair time are fundamental for companies, as the availability of equipment directly depends on this parameter. In this study, a new method for evaluating maintainability during the design phases is proposed. The method is based on the integration of the maintenance task analysis (MTA) principles and the UNE 151001 maintainability evaluation standard. A data structure is proposed that serves the application of the UNE151001 procedures, obtaining a data-based maintainability evaluation. As a validation procedure, an application of the proposed approach is presented using two overhead cranes. Comparisons and recommendations are made regarding the maintainability of both pieces of equipment. Finally, some managerial and engineering insights are presented. Full article

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

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24 pages, 7739 KiB

Open AccessArticle

MT-SIPP: An Efficient Collision-Free Multi-Chain Robot Path Planning Algorithm

by Jinchao Miao, Ping Li, Chuangye Chen, Jiya Tian and Liwei Yang

Machines 2024, 12(7), 482; https://doi.org/10.3390/machines12070482 - 17 Jul 2024

Viewed by 325

Abstract

Compared to traditional multi-robot path planning problems, multi-chain robot path planning (MCRPP) is more challenging because it must account for collisions between robot units and between the bodies of a chain and the leading unit during towing. To address MCRPP more efficiently, we [...] Read more.

Compared to traditional multi-robot path planning problems, multi-chain robot path planning (MCRPP) is more challenging because it must account for collisions between robot units and between the bodies of a chain and the leading unit during towing. To address MCRPP more efficiently, we propose a novel algorithm called Multi-Train Safe Interval Path Planning (MT-SIPP). Based on safe interval path planning principles, we categorize conflicts in the multi-train planning process into three types: travel conflicts, waiting conflicts, and station conflicts. To handle travel conflicts, we use an improved k-robust method to ensure trains avoid collisions with other trains during movement. To resolve waiting conflicts, we apply a time correction method to ensure the safety of positions occupied by trains during waiting periods. To address station conflicts, we introduce node constraints to prevent other trains from occupying the station positions of trains that have reached their target stations and are stopped. Experimental results on three benchmark maps show that the MT-SIPP algorithm achieves about a 30% improvement in solution success rate and nearly a 50% increase in the maximum number of solvable instances compared to existing methods. These results confirm the effectiveness of MT-SIPP in addressing the challenges of MCRPP. Full article

(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)

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33 pages, 23835 KiB

Open AccessArticle

Study on Rubbing-Induced Vibration Characteristics Considering the Flexibility of Coated Casings and Blades

by Yong Zhang, Shuhua Yang, Xingyu Tai, Hui Ma, Hong Guan, Qinqin Mu, Lin Qu and Xiangfu Ding

Machines 2024, 12(7), 481; https://doi.org/10.3390/machines12070481 - 17 Jul 2024

Viewed by 329

Abstract

Rubbing between a blade and its coated casing is one of the main failures in aero-engine systems. This paper aims to study the effects of coated casings on rubbing-induced dynamic responses considering the flexibility of the coated casing and the flexibility of the [...] Read more.

Rubbing between a blade and its coated casing is one of the main failures in aero-engine systems. This paper aims to study the effects of coated casings on rubbing-induced dynamic responses considering the flexibility of the coated casing and the flexibility of the blade. Firstly, an actual compressor blade is established by the shell element and verified by the experiment and ANSYS 19.2 software. Subsequently, a new dynamic model for the coated casing is proposed based on the laminated shell element, and the proposed dynamic model for the coated casing is verified by comparing the natural characteristics calculated by ANSYS software. Moreover, a comprehensive analysis is conducted to analyze the influences of the casing model, coating parameters, and casing parameters on vibration characteristics. Finally, the results show that the coating can diminish the severity level of rubbing. Notably, the material and thickness of the coating can change the nodal diameter vibrations of the casings (NDVCs) induced by rubbing. This study provides valuable guidance for the optimization and design of blade–casing systems. Full article

(This article belongs to the Topic Nonlinear Phenomena, Chaos, Control and Applications to Engineering and Science and Experimental Aspects of Complex Systems)

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25 pages, 9226 KiB

Open AccessArticle

Development of Standalone Extended-Reality-Supported Interactive Industrial Robot Programming System

by Andrija Devic, Jelena Vidakovic and Nikola Zivkovic

Machines 2024, 12(7), 480; https://doi.org/10.3390/machines12070480 - 17 Jul 2024

Viewed by 333

Abstract

Extended reality (XR) is one of the most important technologies in developing a new generation of human–machine interfaces (HMIs). In this study, the design and implementation of a standalone interactive XR-supported industrial robot programming system using the Unity game engine is presented. The [...] Read more.

Extended reality (XR) is one of the most important technologies in developing a new generation of human–machine interfaces (HMIs). In this study, the design and implementation of a standalone interactive XR-supported industrial robot programming system using the Unity game engine is presented. The presented research aims to achieve a cross-platform solution that enables novel tools for robot programming, trajectory validation, and robot programming debugging within an extended reality environment. From a robotics perspective, key design tasks include modeling in the Unity environment based on robot CAD models and control design, which include inverse kinematics solution, trajectory planner development, and motion controller set-up. Furthermore, the integration of real-time vision, touchscreen interaction, and AR/VR headset interaction are involved within the overall system development. A comprehensive approach to integrating Unity with established industrial robot modeling conventions and control strategies is presented. The proposed modeling, control, and programming concepts, procedures, and algorithms are verified using a 6DoF robot with revolute joints. The benefits and challenges of using a standalone XR-supported interactive industrial robot programming system compared to integrated Unity–robotics development frameworks are discussed. Full article

(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)

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20 pages, 3921 KiB

Open AccessArticle

Design of Mixing Device Shafts Based on a Proposed Calculation Method Supported by Finite Element Method Analysis

by Luminita Bibire, Alexandra-Dana Chitimus and Vlad Ciubotariu

Machines 2024, 12(7), 479; https://doi.org/10.3390/machines12070479 - 16 Jul 2024

Viewed by 305

Abstract

The elasticity of bearings as well as their clearance have an essential influence on the total arrow and, therefore, on their own pulsation. In most of the literature, this elasticity is neglected in the calculation of shaft deflections. In some work, the elasticity [...] Read more.

The elasticity of bearings as well as their clearance have an essential influence on the total arrow and, therefore, on their own pulsation. In most of the literature, this elasticity is neglected in the calculation of shaft deflections. In some work, the elasticity of the bearings has been taken into account when calculating the deflection of the mixing device shaft, but this has been carried out on the basis of a high degree of customization: the behavior of the bearings has been considered linearly elastic, which does not correspond to reality because according to the elastic response of the bearing, it is a nonlinear function of the radial displacement. When the shaft of a mixing device operates in a pressure vessel, at the outlet of the pressure vessel, the shaft is provided with a sealing device, which can be considered a third bearing. This aspect is also not taken into account in the calculation of the shaft’s deflection, which leads to a certain degree of error in its determination. This study aims to highlight the influence of the elasticity of the bearings and the sealing device on the stiffness of the shaft and to propose a method that supports a calculation program for calculating the elastic line of a vertical cantilever shaft, considering the role played by the bearings in the case that they behave nonlinearly and the sealing device as the third bearing. This problem was solved both by applying our own method and with the help of the FEM. Full article

(This article belongs to the Special Issue Selected Papers from OPROTEH 2023: 18th International Conference of Constructive Design and Technological Optimization in Machine Building)

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26 pages, 21888 KiB

Open AccessArticle

The Control of Handling Stability for Four-Wheel Steering Distributed Drive Electric Vehicles Based on a Phase Plane Analysis

by Guanfeng Wang and Qiang Song

Machines 2024, 12(7), 478; https://doi.org/10.3390/machines12070478 - 16 Jul 2024

Viewed by 334

Abstract

For the sake of enhancing the handling and stability of distributed drive electric vehicles (DDEVs) under four-wheel steering (4WS) conditions, this study proposes a novel hierarchical control strategy based on a phase plane analysis. This approach involves a meticulous comparison of the stable [...] Read more.

For the sake of enhancing the handling and stability of distributed drive electric vehicles (DDEVs) under four-wheel steering (4WS) conditions, this study proposes a novel hierarchical control strategy based on a phase plane analysis. This approach involves a meticulous comparison of the stable region in the phase plane to thoroughly analyze the intricate influence of the front wheel angle, rear wheel angle, road adhesion coefficient, and longitudinal speed on the complex dynamic performances of DDEVs and to accurately determine the critical stable-state parameter. Subsequently, a hierarchical control strategy is presented as an integrated solution to achieve the coordinated control of maneuverability and stability. On the upper control level, a model predictive control (MPC) motion controller is developed, wherein the real-time adjustment of the control weight matrix is ingeniously achieved by incorporating the crucial vehicle stable-state parameter. The lower control level is responsible for the optimal torque allocation among the four wheel motors to minimize the tire load rate, thereby ensuring a sufficient tire grip margin. The optimal torque distribution for the four wheel motors is achieved using a sophisticated two-level allocation algorithm, wherein the friction ellipse is employed as a judgement condition. Finally, this developed control strategy is thoroughly validated through co-simulation utilizing the CarSim 2019 and Simulink 2020b commercial software, demonstrating the validity of the developed control strategy. The comparative results indicate that the presented controller ensures a better tracking capability to the desired vehicle state while exhibiting improved handling stability under both the double lane shifting condition and the serpentine working condition. Full article

(This article belongs to the Section Vehicle Engineering)

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16 pages, 3227 KiB

Open AccessArticle

Determination of Energy Losses of the Crank Press Mechanism

by Jan Hlavac and Jiri Dekastello

Machines 2024, 12(7), 477; https://doi.org/10.3390/machines12070477 - 15 Jul 2024

Viewed by 366

Abstract

This paper focuses on determining the friction energy loss in the mechanism of a mechanical crank press. After defining the crank press mechanism and how it works, we describe the energy balance of a technological operation—forming. Four distinct methodologies for calculating friction loss [...] Read more.

This paper focuses on determining the friction energy loss in the mechanism of a mechanical crank press. After defining the crank press mechanism and how it works, we describe the energy balance of a technological operation—forming. Four distinct methodologies for calculating friction loss in the mechanism are then presented, namely an empirical method, a spreadsheet calculation utilising force decomposition in a crank mechanism, an analytical calculation of the dynamic behaviour of a press, and a multibody simulation. Each additional approach expands the possibilities for approaching reality, but as the primary aim of the study is to compare the approaches, these possibilities are not exploited. Multibody simulation has proved itself to be accurate and suitable for simulating press mechanisms and investigating their dynamics. Multibody simulation is a much more powerful tool that can lead to a digital twin, which can help us to develop a less energy-demanding press. Confirmation of the multibody simulation results is the main outcome of the comparison and will be used in future work. Full article

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

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17 pages, 21683 KiB

Open AccessArticle

Brush Seal Performance with Ideal Gas Working Fluid under Static Rotor Condition

by Altyib Abdallah Mahmoud Ahmed, Meihong Liu, Yuchi Kang, Juan Wang, Aboubaker I. B. Idriss and Nguyen Thi Trung Tin

Machines 2024, 12(7), 476; https://doi.org/10.3390/machines12070476 - 15 Jul 2024

Viewed by 462

Abstract

The study investigated how variations in pressure ratio affect the leakage flow of a brush seal for both contact and clearance structures, in which the clearance is measured as the distance between the bristles tip and the rotor surface. This investigation utilized the [...] Read more.

The study investigated how variations in pressure ratio affect the leakage flow of a brush seal for both contact and clearance structures, in which the clearance is measured as the distance between the bristles tip and the rotor surface. This investigation utilized the Reynolds-Averaged-Navier–Stokes (RANS) equations alongside a two-dimensional axisymmetric anisotropic porous medium model. To verify the model’s accuracy and dependability, the obtained results were compared with previous numerical results and experimental observations, showing a satisfactory level of agreement. The results indicate that the predominant pressure drop occurs downstream of the bristle pack with the clearance model exhibiting a higher leakage rate compared to the contact model. Leakage increases proportionally with the pressure ratio, while axial velocity gradually rises and radial velocity experiences a significant increase. In conclusion, the leakage in the brush seal contact structure is significantly lower than in the clearance structure, resulting in the best performance. Full article

(This article belongs to the Section Turbomachinery)

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13 pages, 6678 KiB

Open AccessArticle

A Study on Micro-Pit Texture Parameter Optimization and Its Tribological Properties

by Yazhou Mao, Yuxuan Zhang, Jingyang Zheng, Lilin Li, Yuchun Huang, Shaolin Shi, Linyuan Wang, Jiaming Pei and Zichen Li

Machines 2024, 12(7), 475; https://doi.org/10.3390/machines12070475 - 15 Jul 2024

Viewed by 403

Abstract

In this paper, the effect of micro-dimple textures (produced by a laser) on the tribological properties of bearings is investigated. This study offers guidelines to reduce the friction torque of the bearing pair and addresses the problem of difficult start-ups after shutdowns. Micro-pits [...] Read more.

In this paper, the effect of micro-dimple textures (produced by a laser) on the tribological properties of bearings is investigated. This study offers guidelines to reduce the friction torque of the bearing pair and addresses the problem of difficult start-ups after shutdowns. Micro-pits with different texture diameters and depths were machined on the surface of journal bearings. Then, the impact of several different texture parameters on the tribological performance of the bearing pairs was studied using an orthogonal experimental design. Subsequently, the surface morphology of the bearings before and after the friction and wear test was observed using scanning electron microscopy (SEM) and energy-dispersive spectrometry (EDS). These observations were then used to determine the type/state of friction and wear, which also improves our understanding of how texture affects the service life of bearings. The results indicate that the bearings’ micro-pit surface hardness follows an approximate parabolic spatial distribution that decreases along the micro-pit wall. Furthermore, the laser processing of surface textures was found to cause hardening in certain areas, and the chemical composition of elemental carbon and oxygen at the inner surface of processed bearings increased by 31.1% and 7.9%, respectively. Moreover, abrasive wear was identified as the primary form of wear. The textured surface’s antifriction mechanism primarily functioned to trap particles, which acted as a secondary lubrication source and altered the lubrication states by serving as a medium for supplied lubricants. The results confirm that a suitable selection of texture parameters can not only effectively reduce the friction coefficient without shortening the service life of the bearing pair but also facilitate the smooth start-up of the rotor–bearing system. Full article

(This article belongs to the Section Friction and Tribology)

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17 pages, 3619 KiB

Open AccessArticle

The State of Health of Electrical Connectors

by Jian Song, Abhay Shukla and Roman Probst

Machines 2024, 12(7), 474; https://doi.org/10.3390/machines12070474 - 14 Jul 2024

Viewed by 360

Abstract

For modern machines, factories and electric and autonomous vehicles, the importance of vreliable electrical connectors cannot be overstated. With an increasing number of connectors being used in machines, factories and vehicles, ensuring their reliability is crucial for comfort and safety alike. One of [...] Read more.

For modern machines, factories and electric and autonomous vehicles, the importance of vreliable electrical connectors cannot be overstated. With an increasing number of connectors being used in machines, factories and vehicles, ensuring their reliability is crucial for comfort and safety alike. One of the key indicators of reliability is the lifetime of connectors. To evaluate the lifetime of electrical connectors, a testing method and a model for calculating their lifetime based on the test data were developed. The results from these tests were compared to failure analysis data from long-term field operations. The findings indicate that the laboratory tests can accurately reproduce the main failures observed in the field. However, such lifetime tests can be time- and labor-intensive. To address this challenge, a data-driven method is proposed that predicts the lifetime of electrical connectors using statistical analysis of electrical contact resistance data collected from short-term tests. The predictions from this method were compared to actual results obtained from long-term tests. A strong correlation was observed between the contact resistance development in short-term tests and the number of failures in later stages of testing. Thus, apart from predicting the lifetime of connectors, this method can also be applied for failure prognosis in real-time operations. Full article

(This article belongs to the Special Issue Intelligent Machinery Fault Diagnosis and Maintenance)

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18 pages, 6785 KiB

Open AccessArticle

Impact of Installation Deviations on the Dynamic Characteristics of the Shaft System for 1 Gigawatt Hydro-Generator Unit

by Gangyun Song, Xingxing Huang, Haijun Li, Zhengwei Wang and Dong Wang

Machines 2024, 12(7), 473; https://doi.org/10.3390/machines12070473 - 12 Jul 2024

Viewed by 396

Abstract

The shaft system, transferring the kinetic energy of water flow into electrical energy, is the most critical component in hydropower plants. Installation deviations of the shaft system for a giant hydro-generator unit can have significant impacts on its dynamic characteristics and overall performance. [...] Read more.

The shaft system, transferring the kinetic energy of water flow into electrical energy, is the most critical component in hydropower plants. Installation deviations of the shaft system for a giant hydro-generator unit can have significant impacts on its dynamic characteristics and overall performance. In this investigation, a three-dimensional geometry of the shaft system of an operating hydro-generator unit prototype with a rated power of 1 GW is established. Then, the calculation model of the shaft system is generated accordingly with tetrahedral and hexahedral elements. By applying different boundary conditions, the finite-element method is used to analyze the influences of installation deviations, including shaft radial misalignment and angular misalignment, on the dynamic characteristics of the shaft system. The calculation results reveal that the installation deviations change the natural frequencies, critical speeds, and mode shapes of the shaft system to a certain degree. The natural frequencies of the backward precession motion with installation deviations are reduced by 23% and 38% for the rated speed and the maximum runaway speed. Furthermore, for the forward precession motion, they increased by 30% and 48%, respectively. The critical speeds for the shaft system with radial and angular deviations are 3.2% and 3% larger than the critical speed of the shaft system without any mounting deviations. The radial and angular installation deviations below the maximum permissible values will not result in the structural performance degradation of the 1 GW hydro-generator shaft system. The conclusion drawn in this research can be used as a valuable reference for installing other rotating machinery. Full article

(This article belongs to the Special Issue Advancements in Machines and Power Converters for Renewable Power Generation)

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14 pages, 2372 KiB

Open AccessArticle

Dual-Arm Obstacle Avoidance Motion Planning Based on Improved RRT Algorithm

by Zhe Dong, Binrui Zhong, Jiahuan He and Zhao Gao

Machines 2024, 12(7), 472; https://doi.org/10.3390/machines12070472 - 12 Jul 2024

Viewed by 372

Abstract

This paper proposes a solution for the cooperative obstacle avoidance path planning problem in dual manipulator arms using an improved Rapidly Exploring Random Tree (RRT) algorithm. The dual manipulator arms are categorized into a main arm and a secondary arm. Initially, the obstacle [...] Read more.

This paper proposes a solution for the cooperative obstacle avoidance path planning problem in dual manipulator arms using an improved Rapidly Exploring Random Tree (RRT) algorithm. The dual manipulator arms are categorized into a main arm and a secondary arm. Initially, the obstacle avoidance path for the master arm is planned in the presence of static obstacles. Subsequently, the poses of the master arm during its movement are treated as dynamic obstacles for planning the obstacle avoidance path for the slave arm. A cost function incorporating a fast convergence policy is introduced. Additionally, adaptive weights between distance cost and variation cost are innovatively integrated into the cost function, along with increased weights for each joint, enhancing the algorithm’s effectiveness and feasibility in practical scenarios. The smoothness of the planned paths is improved through the introduction of interpolation functions. The improved algorithm is numerically modeled and simulated in MATLAB. The verification results demonstrate that the improved RRT algorithm proposed in this paper is both feasible and more efficient. Full article

(This article belongs to the Special Issue Recent Progress in Multi-Robot Systems)

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19 pages, 2923 KiB

Open AccessArticle

Reinforcement Learning-Based Auto-Optimized Parallel Prediction for Air Conditioning Energy Consumption

by Chao Gu, Shentao Yao, Yifan Miao, Ye Tian, Yuru Liu, Zhicheng Bao, Tao Wang, Baoyu Zhang, Tao Chen and Weishan Zhang

Machines 2024, 12(7), 471; https://doi.org/10.3390/machines12070471 - 12 Jul 2024

Viewed by 370

Abstract

Air conditioning contributes a high percentage of energy consumption over the world. The efficient prediction of energy consumption can help to reduce energy consumption. Traditionally, multidimensional air conditioning energy consumption data could only be processed sequentially for each dimension, thus resulting in inefficient [...] Read more.

Air conditioning contributes a high percentage of energy consumption over the world. The efficient prediction of energy consumption can help to reduce energy consumption. Traditionally, multidimensional air conditioning energy consumption data could only be processed sequentially for each dimension, thus resulting in inefficient feature extraction. Furthermore, due to reasons such as implicit correlations between hyperparameters, automatic hyperparameter optimization (HPO) approaches can not be easily achieved. In this paper, we propose an auto-optimization parallel energy consumption prediction approach based on reinforcement learning. It can parallel process multidimensional time series data and achieve the automatic optimization of model hyperparameters, thus yielding an accurate prediction of air conditioning energy consumption. Extensive experiments on real air conditioning datasets from five factories have demonstrated that the proposed approach outperforms existing prediction solutions, with an increase in average accuracy by 11.48% and an average performance improvement of 32.48%. Full article

(This article belongs to the Special Issue Machine Learning for Predictive Maintenance)

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11 pages, 9905 KiB

Open AccessArticle

Material Extrusion 3D Printing of Micro-Porous Copper-Based Structure for Water Filters

by Nikola Kotorčević, Strahinja Milenković, Fatima Živić, Branka Jordović, Dragan Adamović, Petar Todorović and Nenad Grujović

Machines 2024, 12(7), 470; https://doi.org/10.3390/machines12070470 - 12 Jul 2024

Viewed by 350

Abstract

This paper presents 3D-printed micro-porous structures made of a Cu/PLA composite by using material extrusion 3D printing technology. A metallic filament made of 80% copper and 20% polylactic acid (PLA) was used for the 3D printing of the porous samples. We varied printing [...] Read more.

This paper presents 3D-printed micro-porous structures made of a Cu/PLA composite by using material extrusion 3D printing technology. A metallic filament made of 80% copper and 20% polylactic acid (PLA) was used for the 3D printing of the porous samples. We varied printing parameters, aiming to obtain a micro-range porosity that can serve as a water-filtering structure. The produced samples were analyzed from the aspects of dimensional accuracy, level of porosity, and capacity for water flow. Several samples were fabricated, and the water flow was exhibited for the samples with an approximate 100 µm size of the interconnected open porosity. The application of material extrusion 3D printing, as a cost-effective, widely available technology for producing micro-range porous structures, is still challenging, especially for interconnected predefined porosity with metal-based filaments. Our research showed that the optimization of 3D printing parameters can enable the fabrication of copper-based micro-porous structures, but further research is still needed. Full article

(This article belongs to the Special Issue Recent Advances in 3D Printing in Industry 4.0)

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16 pages, 2383 KiB

Open AccessArticle

Novel Intelligent Traffic Light Controller Design

by Firas Zahwa, Chi-Tsun Cheng and Milan Simic

Machines 2024, 12(7), 469; https://doi.org/10.3390/machines12070469 - 11 Jul 2024

Viewed by 360

Abstract

Efficient traffic flow management at intersections is vital for optimizing urban transportation networks. This paper presents a comprehensive approach to refining traffic flow by analyzing the capacity of roads and integrating fuzzy logic-based traffic light control systems. We examined the capacity of roads [...] Read more.

Efficient traffic flow management at intersections is vital for optimizing urban transportation networks. This paper presents a comprehensive approach to refining traffic flow by analyzing the capacity of roads and integrating fuzzy logic-based traffic light control systems. We examined the capacity of roads connecting intersections, considering factors such as road vehicle capacity, vehicle speed, and traffic flow volume, through detailed mathematical modeling and analysis. Control is determined by the maximum capacity of each road segment, providing valuable insights into traffic flow dynamics. Building upon this capacity and flow analysis, the research introduces a novel intelligent traffic light controller (ITLC) system based on fuzzy logic principles. By incorporating real-time traffic data and leveraging fuzzy logic algorithms, our ITLC system dynamically adjusts traffic light timings to optimize vehicle flow at two intersections. The paper discusses the design and implementation of the ITLC system, highlighting its adaptive capabilities in response to changing traffic conditions. Simulation results demonstrate the effectiveness of the ITLC system in improving traffic flow and reducing congestion at intersections. Furthermore, this research provides an analysis of the mathematical models used to calculate road capacity, offering insights into the underlying principles of traffic flow optimization. Through the simulation, we have validated the accuracy and reliability of our controller. Full article

(This article belongs to the Section Vehicle Engineering)

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21 pages, 10992 KiB

Open AccessArticle

Detection of Demagnetization Faults in Electric Motors by Analyzing Inverter Based Current Data Using Machine Learning Techniques

by Daniel Walch, Christoph Blechinger, Martin Schellenberger, Maximilian Hofmann, Bernd Eckardt and Vincent R.H. Lorentz

Machines 2024, 12(7), 468; https://doi.org/10.3390/machines12070468 - 11 Jul 2024

Viewed by 362

Abstract

Demagnetization of the rotor magnets is a significant failure mode that can occur in permanent magnet synchronous machines (PMSMs). Early detection of demagnetization faults can help change system parameters to reduce power output or ensure safety. In this paper, the effects of demagnetization [...] Read more.

Demagnetization of the rotor magnets is a significant failure mode that can occur in permanent magnet synchronous machines (PMSMs). Early detection of demagnetization faults can help change system parameters to reduce power output or ensure safety. In this paper, the effects of demagnetization faults were analyzed both in simulation and experiments using the example of drone motors. An approach was investigated to detect even minor demagnetization faults that does not require any additional sensing effort. Machine learning (ML) techniques are used to analyze the phase current data directly received from the inverter to enable anomaly detection. For this purpose, the phase current is transformed by the Fast Fourier Transform (FFT), the spectral data is then reduced in dimensionality, followed by an anomaly detection algorithm using a one-class support vector machine (OC-SVM). To ensure simplified initialization of the ML model without the need for training sets of damaged drives, only data from magnetically undamaged motors was used to train the models for anomaly detection. Different selections of considered harmonics and different metrics were investigated using the experimental data, achieving a precision of up to 99%, a specificity of up to 98%, and an accuracy of up to 90%. Full article

(This article belongs to the Section Electrical Machines and Drives)

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13 pages, 722 KiB

Open AccessArticle

Efficiency Analysis of Die Attach Machines Using Overall Equipment Effectiveness Metrics and Failure Mode and Effects Analysis with an Ishikawa Diagram

by Rex Revian A. Guste, Klint Allen A. Mariñas and Ardvin Kester S. Ong

Machines 2024, 12(7), 467; https://doi.org/10.3390/machines12070467 - 11 Jul 2024

Viewed by 473

Abstract

The semiconductor manufacturing sector has contributed to the advancement of technical development in the sphere of industrial applications, but one crucial factor that cannot be overlooked is the evaluation of a machine’s state. Despite the presence of advanced equipment, data on their performances [...] Read more.

The semiconductor manufacturing sector has contributed to the advancement of technical development in the sphere of industrial applications, but one crucial factor that cannot be overlooked is the evaluation of a machine’s state. Despite the presence of advanced equipment, data on their performances are not properly reviewed, resulting in a variety of concerns such as high rejection rates, lower production output, manufacturing overhead cost issues, and customer complaints. This study’s goal is to evaluate the performance of die attach machines made by a prominent subcontractor semiconductor manufacturing business in the Philippines; our findings will provide other organizations with important insights into the appropriate diagnosis of productivity difficulties via productivity metrics analyses. The study focuses on a specific type of die attach machine, with machine 10 showing to be the most troublesome, with an overall equipment effectiveness (OEE) rating of 43.57%. The Failure Mode and Effects Analysis (FMEA) identified that the primary reasons for the issue were idling, small stoppages, and breakdown loss resulting from loosened screws in the work holder. The risk priority number (RPN) was calculated to be 392, with a severity level of 7, an occurrence level of 7, and a detection level of 8. The findings provide new insight into the methods that should be included in the production process to boost efficiency and better suit the expectations of customers in a highly competitive market. Full article

(This article belongs to the Special Issue Advances in Machinery Condition Monitoring, Diagnosis and Prognosis)

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18 pages, 5103 KiB

Open AccessArticle

Failure Inducement Factor Analysis and Optimal Design Method of Ball Bearing Cage for Aviation Motor

by Yongcun Cui, Linshen Cai, Jingjing Wang and Xiaoguo Gao

Machines 2024, 12(7), 466; https://doi.org/10.3390/machines12070466 - 10 Jul 2024

Viewed by 291

Abstract

In experiments of aviation motor bearings, when the deep-groove ball bearings are subjected to an overturning moment at high speed, it often happens that the rivet on the cage breaks and the debris invades the raceway, resulting in bearing failure. To address the [...] Read more.

In experiments of aviation motor bearings, when the deep-groove ball bearings are subjected to an overturning moment at high speed, it often happens that the rivet on the cage breaks and the debris invades the raceway, resulting in bearing failure. To address the problem of early failure of deep-groove ball bearing cages and rivets in aviation motors, the causes of early failure were analyzed from the aspect of cage design in this study. The influence of the raceway and cage structure parameters on the dynamic contact characteristics of the rolling element and cage under the action of overturning torque were analyzed, the weak link of the cage was determined, and the cage design parameters were optimized. The results show that with an increase in the cage width and pocket radius, the impact force between the ball and cage first decreases and then increases, and the tilt angle of the cage gradually decreases. A larger channel radius and smaller clearance can slow down the interaction between the cage and the rolling element and make the cage run more smoothly. Increasing the thickness of the cage can ensure that the rivet part of the cage is at a low stress level, and the risk of premature fatigue failure at the rivet part can be reduced by maintaining a small gap–fit relationship between the rivet and rivet holes. The research results indicate that the working condition adaptability of the bearing cage for aviation motors can be improved, and the design method for this type of bearing can be enhanced. Full article

(This article belongs to the Section Electrical Machines and Drives)

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Machines, Volume 12, Issue 7 (July 2024) – 69 articles

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