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Machines, Volume 12, Issue 6 (June 2024) – 74 articles

Cover Story (view full-size image): Dexterous manipulation of unknown objects using mechanical hands is a challenge; the main difficulties arise from the absence of precise models of the manipulated objects and limited sensing capabilities of the mechanical hands compared to human hands. This problem was addressed at IOC-UPC by introducing a data-driven approach that provides a learning-based planner for dexterous manipulation employing an Adaptive Neuro-fuzzy Inference System (ANFIS). The proposed planner allows the manipulation of objects of various shapes, sizes, and material properties, providing an adaptive solution to increase robotic dexterity. The planner was validated in real-world scenarios using an Allegro anthropomorphic robotic hand with satisfactory operational outcomes. View this paper
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12 pages, 3649 KiB  
Article
Research on the Consistency Evaluation of the Spindle Unit Stiffness Based on Comprehensive Weights
by Feng Sun, Yu Jiang, Ran Zhou, Qi Zhang, Fangchao Xu, Chuan Zhao, Haining Zhao, Wenhua Yang, Bo Li and Shuang Bai
Machines 2024, 12(6), 426; https://doi.org/10.3390/machines12060426 - 20 Jun 2024
Viewed by 596
Abstract
The spindle unit is the core component of a machine, and its stiffness is a key performance characteristic. The stiffness consistency is a key index to measure the stiffness of spindle units; however, there is a lack of unified evaluation methods for the [...] Read more.
The spindle unit is the core component of a machine, and its stiffness is a key performance characteristic. The stiffness consistency is a key index to measure the stiffness of spindle units; however, there is a lack of unified evaluation methods for the spindle unit stiffness consistency. This paper proposes a comprehensive method for the evaluation of the spindle unit stiffness consistency based on fluctuations and comprehensive weights. First, the consistency of the spindle unit stiffness evaluation indices is expressed based on the fluctuations. Secondly, the subjective and objective weights of the spindle unit stiffness evaluation indices are given based on the AHP and CRITIC weight assignment methods. To obtain the comprehensive weights of the evaluation indices, the subjective and objective weights are synthesized based on the linear weighting method. Then, the consistency level of the spindle unit stiffness is obtained by the weighted summation of the comprehensive weights and fluctuations of the evaluation indices. Finally, the stiffness consistency of a group of spindle units is evaluated based on this method, and the evaluation result shows a 10.63% fluctuation, which indicates that its stiffness consistency level is class B, in line with the factory production requirements. Full article
(This article belongs to the Section Advanced Manufacturing)
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16 pages, 1606 KiB  
Article
Implementation and Possibilities of Fuzzy Logic for Optimal Operation and Maintenance of Marine Diesel Engines
by Hla Gharib and György Kovács
Machines 2024, 12(6), 425; https://doi.org/10.3390/machines12060425 - 20 Jun 2024
Viewed by 890
Abstract
This paper explores the implementation and possibilities of utilizing fuzzy logic theory for optimal operation and early fault detection in marine diesel engines. It emphasizes its role in managing the complexity and ambiguity inherent in engine performance and preventive maintenance. Preventive maintenance is [...] Read more.
This paper explores the implementation and possibilities of utilizing fuzzy logic theory for optimal operation and early fault detection in marine diesel engines. It emphasizes its role in managing the complexity and ambiguity inherent in engine performance and preventive maintenance. Preventive maintenance is crucial for ensuring the reliability and longevity of marine diesel engines. Implementing fuzzy logic control (FLC) systems can enhance the preventive maintenance strategies for these engines, leading to reduced downtime, lower maintenance costs, and improved overall performance. Through a comprehensive literature review and analysis of a case study, this paper demonstrates the adaptability, effectiveness, and transformative potential of fuzzy logic systems. Focusing on applications such as engine speed control, performance improvements, and early fault detection, the paper highlights the implementation of fuzzy logic for enhanced predictive capabilities. The study aims to offer a flexible approach to engine management through fuzzy logic, laying the way for significant improvement in optimal marine diesel engine operation. Full article
(This article belongs to the Special Issue Intelligent Machinery Fault Diagnosis and Maintenance)
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18 pages, 6289 KiB  
Article
Tacholess Time Synchronous Averaging for Gear Fault Diagnosis in Wind Turbine Gearboxes Using a Single Accelerometer
by Trong-Du Nguyen, Huu-Cuong Nguyen, Van-Minh-Hoang Nguyen and Phong-Dien Nguyen
Machines 2024, 12(6), 424; https://doi.org/10.3390/machines12060424 - 20 Jun 2024
Cited by 1 | Viewed by 1156
Abstract
Wind power is increasingly seen as a global, sustainable, and eco-friendly energy option. However, one significant obstacle to further wind energy investment is the high failure rate of wind turbines. The gearbox plays a pivotal role in turbine performance. In recent years, there [...] Read more.
Wind power is increasingly seen as a global, sustainable, and eco-friendly energy option. However, one significant obstacle to further wind energy investment is the high failure rate of wind turbines. The gearbox plays a pivotal role in turbine performance. In recent years, there has been a surge in the focus on gearbox fault diagnosis, reflecting its criticality and prevalence in the industry. Time synchronous averaging (TSA) is a primary technique to identify faults in wind turbine gearboxes using mechanical vibration signals. Generally, implementing TSA requires a device that is capable of recording the phase information of a rotary shaft. Nevertheless, there are situations in which the installation of such a device poses difficulties. For instance, gearboxes that are in use cannot be halted to allow for the installation of a device, and sealed gearboxes provide challenges while being inserted into the device. This research presents an innovative technical way to improve the TSA method without requiring a phase signal. The proposed method has the advantage of extracting the shaft rotation angle signal from the measured acceleration signal, even in non-stationary conditions where the rotational speed varies over time. The effectiveness of the proposed method is validated through measured datasets from wind turbine gearboxes with actual faults and a dataset from a gear system with variable rotational speeds. Full article
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14 pages, 6243 KiB  
Article
Comparison of Electromagnetic Performance in Interior Permanent Magnet Motors with Different Central and Bilateral Bridges
by Baicheng Shao, Wei Cai and Chen Yang
Machines 2024, 12(6), 423; https://doi.org/10.3390/machines12060423 - 19 Jun 2024
Cited by 1 | Viewed by 724
Abstract
Studies on the central and bilateral bridges of interior permanent magnet (IPM) motors often focus on individual mechanical strength or electromagnetic performance, lacking comparative studies on the electromagnetic performance of motors with different central and bilateral bridges under the same mechanical strength. This [...] Read more.
Studies on the central and bilateral bridges of interior permanent magnet (IPM) motors often focus on individual mechanical strength or electromagnetic performance, lacking comparative studies on the electromagnetic performance of motors with different central and bilateral bridges under the same mechanical strength. This paper designs three rotors with different central and bilateral bridges and compares the electromagnetic performance of the three motors. First, to ensure the safe operation of the three rotors at high speeds, the mechanical stress of each rotor has been analyzed using the finite-element method (FEM). Subsequently, the major electromagnetic performances of the three motors are analyzed and compared, including the air-gap flux density, back electromotive force (back-EMF), inductance, salience, torque, power, loss, efficiency, and demagnetization. The results indicate that the rotor without central bridges has the largest leakage flux and the lowest torque but exhibits minimal torque ripple. The rotor with narrower bilateral bridges has the highest torque and maximum torque ripple. The torque performance of the rotor with wider bilateral bridges lies between the two aforementioned motors, and it possesses the highest efficiency. In the end, by adjusting the dimensions of the permanent magnets, the torque of all three models increases, but the motor with narrower bilateral bridges still has the largest torque. These findings provide valuable references for rotor design. Full article
(This article belongs to the Section Electrical Machines and Drives)
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25 pages, 4664 KiB  
Article
Research on the Influence of Radial Variation of Centroid on the Motion of Spherical Robot
by Long Ma, Minggang Li, Rui Chang and Hanxu Sun
Machines 2024, 12(6), 422; https://doi.org/10.3390/machines12060422 - 19 Jun 2024
Viewed by 776
Abstract
Through the pendulum mechanism inside the spherical shell, the centroid can be varied circumferentially, enabling the spherical robot to achieve omnidirectional flexible movement. Additionally, the radial variation ability of the centroid enables spherical robots to adopt two distinct driving modes: the traditional lower [...] Read more.
Through the pendulum mechanism inside the spherical shell, the centroid can be varied circumferentially, enabling the spherical robot to achieve omnidirectional flexible movement. Additionally, the radial variation ability of the centroid enables spherical robots to adopt two distinct driving modes: the traditional lower pendulum driving mode and the inverted pendulum driving mode. There are two manifestations of radial variation in the centroid: having different radial positions of the centroid and achieving radial movement of the centroid. Focusing on these two manifestations, experimental data are obtained through different motion velocities and different motion slopes to conduct research on the influence of radial variation in the centroid on the motion of spherical robots. Based on the experimental data, multiple indicators are analyzed, including response speed, convergence speed, stability, and overshoot, as well as steering ability, climbing ability, and output power. The impact of the radial variation ability of the centroid on the control performance, locomotion capability, and energy consumption of spherical robots is summarized, and the correlation model relating the motion requirements to the radial position of the centroid is established, providing a theoretical basis for the selection of driving modes and centroid positions for spherical robots facing complex task requirements. Full article
(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)
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30 pages, 12505 KiB  
Article
Analysis and Optimization of a Novel Compact Compliant 2-DOF Positioner for Positioning to Assess Bio-Specimen Characteristics
by Minh Phung Dang, Hieu Giang Le, Chi Thien Tran, Vo Duc Trieu Nguyen and Ngoc Le Chau
Machines 2024, 12(6), 421; https://doi.org/10.3390/machines12060421 - 19 Jun 2024
Cited by 2 | Viewed by 789
Abstract
A novel compact 2-DOF compliant positioner is developed for the purpose of achieving good characteristics such as high natural frequency, high displacement amplification ratio, good linear motion, and compact structure based on its symmetrical structure. To be specific, the developed stage is proposed [...] Read more.
A novel compact 2-DOF compliant positioner is developed for the purpose of achieving good characteristics such as high natural frequency, high displacement amplification ratio, good linear motion, and compact structure based on its symmetrical structure. To be specific, the developed stage is proposed according to an advanced six-lever displacement amplifier arranged at an inclination angle of the rigid bar utilizing right circular hinges and a parallel guiding mechanism with integrated flexure leaf hinges to attain the above-mentioned characteristics and reduce the decoupling mobility error. First, to quickly assess the initial quality response, an integration method of kinetostatic analysis, the Lagrange method, and finite element analysis was applied to evaluate and verify the quality characteristic of the stage. The experimental result showed that the error between the analytical method and the FEA method was 1.3%, which was relatively small and reliable for quickly assessing the primary quality response of the proposed positioner. Next, to boost the important output characteristics of the developed positioner, the integration approach of the response surface method and NSGA-II algorithm was utilized to find the optimal design variables. Finally, a prototype was manufactured based on the CNC milling method to validate the experimental and FEA analysis results. The attained results show that the optimal results of safety factor and output displacement were 2.4025 and 248.9 µm. Moreover, the FEA verification results were 2.4989 and 242.16 µm, with errors for safety factor and output displacement between the optimal result and the FEA result of 3.86% and 2.78%, respectively. In addition, the simulation and experimental results of the first natural frequency were 371.83 Hz and 329.59 Hz, respectively, and the error between the FEA result and experimental result for the first natural frequency was 11.36%. Furthermore, the achieved results show that the relationship between input displacement and output displacement of the experimental result and the FEA result of the developed structure achieved a good linear connection. These results suggest that the proposed positioner will be a potential structure employed in precise positioning systems and nanoindentation testing positioning systems for checking bio-specimens’ behaviors. Full article
(This article belongs to the Special Issue Optimization and Design of Compliant Mechanisms)
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13 pages, 5419 KiB  
Article
Design and Test of a 2-DOF Compliant Positioning Stage with Antagonistic Piezoelectric Actuation
by Haitao Wu, Hui Tang and Yanding Qin
Machines 2024, 12(6), 420; https://doi.org/10.3390/machines12060420 - 19 Jun 2024
Cited by 3 | Viewed by 977
Abstract
This paper designs a two-degrees-of-freedom (DOF) compliant positioning stage with antagonistic piezoelectric actuation. Two pairs of PEAs are arranged in an antagonistic configuration to generate reciprocating motions. Flexure mechanisms are intentionally adopted to construct the fixtures for PEAs, whose elastic deformations can help [...] Read more.
This paper designs a two-degrees-of-freedom (DOF) compliant positioning stage with antagonistic piezoelectric actuation. Two pairs of PEAs are arranged in an antagonistic configuration to generate reciprocating motions. Flexure mechanisms are intentionally adopted to construct the fixtures for PEAs, whose elastic deformations can help to reduce the stress concentration on the PEA caused by the extension of the PEA in the other direction. Subsequently, the parameter and performance of the 2-DOF compliant positioning stage is optimized and verified by finite element analysis. Finally, a prototype is fabricated and tested. The experimental results show that the developed positioning stage achieves a working stroke of 28.27 μm × 27.62 μm. Motion resolutions of both axes are 8 nm and natural frequencies in the working directions are up to 2018 Hz, which is promising for high-precision positioning control. Full article
(This article belongs to the Special Issue Optimization and Design of Compliant Mechanisms)
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19 pages, 5885 KiB  
Article
Collaborative Production Planning Based on an Intelligent Unmanned Mining System for Open-Pit Mines in the Industry 4.0 Era
by Kui Liu, Bin Mei, Qing Li, Shuai Sun and Qingping Zhang
Machines 2024, 12(6), 419; https://doi.org/10.3390/machines12060419 - 18 Jun 2024
Cited by 1 | Viewed by 1014
Abstract
Open-pit mining is a cornerstone of industrial raw material extraction, yet it is fraught with safety concerns due to rough operating conditions. The advent of Industry 4.0 has introduced advanced technologies such as AI, the IoT, and autonomous systems, setting the stage for [...] Read more.
Open-pit mining is a cornerstone of industrial raw material extraction, yet it is fraught with safety concerns due to rough operating conditions. The advent of Industry 4.0 has introduced advanced technologies such as AI, the IoT, and autonomous systems, setting the stage for a paradigm shift towards unmanned mining operations. With this study, we addressed the urgent need for safe and efficient production based on intelligent unmanned mining systems in open-pit mines. A collaborative production planning model was developed for an intelligent unmanned system comprising multiple excavators and mining trucks. The model is formulated to optimize multiple objectives, such as total output, equipment idle time, and transportation cost. A multi-objective optimization approach based on the genetic algorithm was employed to solve the model, ensuring a balance among conflicting objectives and identifying the best possible solutions. The computational experiments revealed that the collaborative production planning method significantly reduces equipment idle time and enhances output. Moreover, with the proposed method, by optimizing the configuration to include 6 unmanned excavators, 50 unmanned mining trucks, and 4 unloading points, a 92% reduction in excavator idle time and a 44% increase in total output were achieved. These results show the model’s potential to transform open-pit mining operations by using intelligent planning. Full article
(This article belongs to the Special Issue Key Technologies in Intelligent Mining Equipment)
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25 pages, 8414 KiB  
Article
A Fault Prediction Method for CNC Machine Tools Based on SE-ResNet-Transformer
by Zhidong Wu, Liansheng He, Wei Wang, Yongzhi Ju and Qiang Guo
Machines 2024, 12(6), 418; https://doi.org/10.3390/machines12060418 - 18 Jun 2024
Cited by 1 | Viewed by 1306
Abstract
Aiming at the problem that predicted data do not reflect the operating status of computer numerical control (CNC) machine tools, this article proposes a new combined model based on SE-ResNet and Transformer for CNC machine tool failure prediction. Firstly, the Transformer model is [...] Read more.
Aiming at the problem that predicted data do not reflect the operating status of computer numerical control (CNC) machine tools, this article proposes a new combined model based on SE-ResNet and Transformer for CNC machine tool failure prediction. Firstly, the Transformer model is utilised to build a non-linear temporal feature mapping using the attention mechanism in multidimensional data. Secondly, the predicted data are transformed into 2D features by the SE-ResNet model, which is adept at processing 2D data, and the spatial feature relationships between predicted data are captured, thus enhancing the state recognition capability. Through experiments, data involving the CNC machine tools in different states are collected to build a dataset, and the method is validated. The SE-ResNet-Transformer model can accurately predict the state of CNC machine tools with a recognition rate of 98.56%. Results prove the effectiveness of the proposed method in CNC machine tool failure prediction. The SE-ResNet-Transformer model is a promising approach for CNC machine tool failure prediction. The method shows great potential in improving the accuracy and efficiency of CNC machine tool failure prediction. Feasible methods are provided for precise control of the state of CNC machine tools. Full article
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18 pages, 3726 KiB  
Article
Modeling of Filtration Phenomenon in Hydrostatic Drives
by Klaudiusz Klarecki, Dominik Rabsztyn and Piotr Czop
Machines 2024, 12(6), 417; https://doi.org/10.3390/machines12060417 - 18 Jun 2024
Cited by 1 | Viewed by 884
Abstract
Some users consider modern hydrostatic drives and controls to be unreliable and difficult to maintain. This view is often due to operational problems caused by issues with obtaining and then maintaining the appropriate cleanliness class of the working fluid. Recommendations on the selection [...] Read more.
Some users consider modern hydrostatic drives and controls to be unreliable and difficult to maintain. This view is often due to operational problems caused by issues with obtaining and then maintaining the appropriate cleanliness class of the working fluid. Recommendations on the selection of appropriate filtration system elements can be found in the literature, but there is no numerical model that could be helpful in a detailed analysis of the phenomenon. In the article, the authors tried to fill the research gap regarding the lack of a filtration model based on the filtration efficiency coefficient of filter elements used in hydraulic drives and controls. The developed model allows users to determine the influence of selected filtration system parameters on the separation of contaminants by filter elements. The model is intended to help designers and users of hydraulic drives and controls in optimizing the filtration system in order to obtain and then maintain the required cleanliness class of the hydraulic fluid. This paper also includes the results of the sensitivity analysis of selected filtration-system operating parameters in terms of the highest efficiency. In order to verify the developed model, experimental tests were also carried out, with the results presented in this paper. Based on the numerical analyses and experimental studies, recommendations that may be helpful in the selection or development of filtration systems used in hydrostatic drives and controls were developed. Full article
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33 pages, 5601 KiB  
Review
A Review and Prospects of Manufacturing Process Knowledge Acquisition, Representation, and Application
by Zhongyi Wu and Cheng Liang
Machines 2024, 12(6), 416; https://doi.org/10.3390/machines12060416 - 18 Jun 2024
Cited by 1 | Viewed by 3195
Abstract
The evolution of knowledge acquisition and representation in manufacturing technologies is vital for translating complex manufacturing data into actionable insights and advancing a comprehensive knowledge framework. This framework is pivotal in driving innovation and efficiency in intelligent manufacturing. This review aggregates recent research [...] Read more.
The evolution of knowledge acquisition and representation in manufacturing technologies is vital for translating complex manufacturing data into actionable insights and advancing a comprehensive knowledge framework. This framework is pivotal in driving innovation and efficiency in intelligent manufacturing. This review aggregates recent research on knowledge acquisition and representation within the manufacturing process, addressing existing challenges and mapping potential future developments. It includes an analysis of 123 papers that focus on harnessing advanced intelligent analytics to extract operationally relevant knowledge from the extensive datasets typical in manufacturing environments. The narrative then examines the methodologies for constructing models of knowledge in manufacturing processes and explores their applications in manufacturing principles, design, management, and decision-making. This paper highlights the limitations of current technologies and projects emerging research avenues in the acquisition and representation of process knowledge within intelligent manufacturing systems, with the objective of informing future technological breakthroughs. Full article
(This article belongs to the Section Advanced Manufacturing)
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24 pages, 1464 KiB  
Review
Wearable Assistive Rehabilitation Robotic Devices—A Comprehensive Review
by Pavan Kalyan Lingampally, Kuppan Chetty Ramanathan, Ragavanantham Shanmugam, Lenka Cepova and Sachin Salunkhe
Machines 2024, 12(6), 415; https://doi.org/10.3390/machines12060415 - 17 Jun 2024
Cited by 3 | Viewed by 2619
Abstract
This article details the existing wearable assistive devices that could mimic a human’s active range of motion and aid individuals in recovering from stroke. The survey has identified several risk factors associated with musculoskeletal pain, including physical factors such as engaging in high-intensity [...] Read more.
This article details the existing wearable assistive devices that could mimic a human’s active range of motion and aid individuals in recovering from stroke. The survey has identified several risk factors associated with musculoskeletal pain, including physical factors such as engaging in high-intensity exercises, experiencing trauma, aging, dizziness, accidents, and damage from the regular wear and tear of daily activities. These physical risk factors impact vital body parts such as the cervical spine, spinal cord, ankle, elbow, and others, leading to dysfunction, a decrease in the range of motion, and diminished coordination ability, and also influencing the ability to perform the activities of daily living (ADL), such as speaking, breathing and other neurological responses. An individual with these musculoskeletal disorders requires therapies to regain and restore the natural movement. These therapies require an experienced physician to treat the patient, which makes the process expensive and unreliable because the physician might not repeat the same procedure accurately due to fatigue. These reasons motivated researchers to develop and control robotics-based wearable assistive devices for various musculoskeletal disorders, with economical and accessible solutions to aid, mimic, and reinstate the natural active range of motion. Recently, advancements in wearable sensor technologies have been explored in healthcare by integrating machine-learning (ML) and artificial intelligence (AI) techniques to analyze the data and predict the required setting for the user. This review provides a comprehensive discussion on the importance of personalized wearable devices in pre- and post-clinical settings and aids in the recovery process. Full article
(This article belongs to the Special Issue Design and Application of Medical and Rehabilitation Robots)
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16 pages, 14166 KiB  
Article
Identification of Heat Transfer Parameters for Gravity Sand Casting Simulations
by Alberto Vergnano, Pietro Facondini, Nicolò Morselli, Paolo Veronesi and Francesco Leali
Machines 2024, 12(6), 414; https://doi.org/10.3390/machines12060414 - 17 Jun 2024
Viewed by 846
Abstract
Gravity sand casting simulations require accurate modelling of heat transfer phenomena to reliably evaluate the expected quality of the produced parts. Average model parameters can be easily retrieved from a validated database. However, these parameters are highly dependent on the specific sand used [...] Read more.
Gravity sand casting simulations require accurate modelling of heat transfer phenomena to reliably evaluate the expected quality of the produced parts. Average model parameters can be easily retrieved from a validated database. However, these parameters are highly dependent on the specific sand used and the actual forming process in the foundry. Furthermore, the heat transfer from the solidifying alloy to the mould surfaces is not precisely known, so simulation models usually use typical values for overall heat transfer coefficients. Most research works investigate individual parameters, whereas heat transfer phenomena largely arise from their interaction together. Therefore, the present work describes a combined experimental and computational method based on genetic algorithm techniques for determining the most important parameters for heat transfer in a sand mould. The experiments examine both virgin and reused sand, as these are alternatively used in the foundry for mould forming. The density, thermal conductivity, and specific heat capacity of the different sands are identified, along with heat transfer coefficients. The counterproof simulations demonstrate that the standard parameters are quite reliable for virgin sand. However, in the case of reused sand, the identified parameters lead to more reliable results. Full article
(This article belongs to the Special Issue Advances in Design and Manufacturing in Die Casting and Metal Forming)
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12 pages, 3939 KiB  
Article
Young’s Modulus and Hardness Identification of Extruded Aluminum by Scratching Damper
by Chun-Nam Wong, Anand Vyas, Wai-On Wong and Ruqi Sun
Machines 2024, 12(6), 413; https://doi.org/10.3390/machines12060413 - 17 Jun 2024
Viewed by 972
Abstract
A special vibration damper is proposed for Young’s modulus and hardness identification through a scratching process on extruded aluminum. This paper presents the design and working principle of a scratching damper based on a scratching device. A non-contact electromagnetic shaker is used to [...] Read more.
A special vibration damper is proposed for Young’s modulus and hardness identification through a scratching process on extruded aluminum. This paper presents the design and working principle of a scratching damper based on a scratching device. A non-contact electromagnetic shaker is used to generate the shaking force for test sample vibration. The required forces on the scratched material during the scratching process are generated by an adjustable compression spring. The proposed damper is designed and tested on an extruded aluminum 3004 sample for the determination of its Young’s modulus and hardness, and validation is performed using the standard test instruments. The physical dimensions of the scratching tracks are measured using a microscope and utilized to compute the scratching energy factor. Load curves are obtained at different divisions of the scratching process. The loop energy during the scratching process of the tested object is measured and used for the determination of sample material properties. Furthermore, the energy conservation law, scratch energy release rate of semi-conical scratch head, and loop energy release rate are established to determine the Young’s modulus and hardness of the sample. Their estimation accuracies are evaluated. The proposed method has several advantages over the traditional methods, including low cost, directness, and high repeatability. The results suggest this to be used as an alternative to the standard modulus and hardness tester. Full article
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11 pages, 5672 KiB  
Communication
A Study on New Straight Shape Design to Reduce Cogging Torque of Small Wind Power Generator
by Junho Kang, Ju Lee, Sanghwan Ham, Yondo Chun and Hyunwoo Kim
Machines 2024, 12(6), 412; https://doi.org/10.3390/machines12060412 - 15 Jun 2024
Cited by 2 | Viewed by 1050
Abstract
In this paper, a 150 W small wind power generator which has a permanent magnet synchronous generator type is proposed with a new straight shape stator and rotor to reduce the cogging torque. The advantages of the proposed structure are introduced through a [...] Read more.
In this paper, a 150 W small wind power generator which has a permanent magnet synchronous generator type is proposed with a new straight shape stator and rotor to reduce the cogging torque. The advantages of the proposed structure are introduced through a comparison between the basic and the proposed models. By comparing the pole slot combination of the proposed generator, the combination with optimal cogging torque characteristics was selected. The electromagnetic characteristics of the proposed shape are analyzed for design variables using a finite element analysis of ANSYS 2021 R1 Maxwell. The final model of the proposed structure is designed by considering the cogging torque and electromagnetic characteristics of the generator. The electromagnetic and structural simulations of the final model are performed to satisfy the required performance of the generator and mechanical safety. To verify the FEA results of the final model, a prototype is manufactured, experimented, and compared with the FEA results. Full article
(This article belongs to the Topic Advanced Electrical Machine Design and Optimization Ⅱ)
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18 pages, 1853 KiB  
Article
Empowering Manufacturing Environments with Process Mining-Based Statistical Process Control
by Onur Dogan and Ourania Areta Hiziroglu
Machines 2024, 12(6), 411; https://doi.org/10.3390/machines12060411 - 15 Jun 2024
Cited by 1 | Viewed by 1467
Abstract
The production of high-quality products and efficient manufacturing processes in modern environments, where processes vary widely, is one of the most crucial issues today. Statistical process control (SPC) and process mining (PM) effectively trace and enhance the manufacturing processes. In this direction, this [...] Read more.
The production of high-quality products and efficient manufacturing processes in modern environments, where processes vary widely, is one of the most crucial issues today. Statistical process control (SPC) and process mining (PM) effectively trace and enhance the manufacturing processes. In this direction, this paper proposes an innovative approach involving SPC and PM strategies to empower the manufacturing environment. SPC monitors key performance indicators (KPIs) and identifies out-of-control processes that deviate from specification limits, while PM discovery techniques are applied for those abnormal processes to extract the actual process flow from event logs and model it using Petri nets. Different enhancement techniques in PM, such as decision rules and root cause analysis, are then used to return the process to control and prevent future deviations. The application of the integrated SPC–PM approach is shown through case studies of production processes. SPC charts found that over 6% of processes exceeded specification limits. At the same time, PM methodologies revealed that prolonged times for the ‘Quality Control’ activity is the fundamental factor increasing the cycle time. Moreover, decision tree analysis provides rules for decreasing the cycle times of unbalanced processes. The absence of a transition from the ‘Return from Waiting’ activity to ‘Packing and Shipment’ is a critical factor in decreasing cycle times, as is the shift information. Our newly proposed methodology, which combines process analysis from PM with statistical monitoring from SPC, ensures operational excellence and consistent quality in manufacturing. This study illustrates the application of the proposed methodology through a case study in production processes, highlighting its effectiveness in identifying and addressing process deviations. Full article
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26 pages, 13253 KiB  
Article
The Design of Decoupled Robotic Arm Based on Chain Transmission
by Ziling Ma, Chuan Ding, Lijian Li and Baoqiang Tian
Machines 2024, 12(6), 410; https://doi.org/10.3390/machines12060410 - 15 Jun 2024
Viewed by 1128
Abstract
Unlike the conventional robotic arm where the joints are coupled to each other, this paper proposes a position and posture decoupling method to mechanically correct the end position of the robotic arm in real time through dual-motion transmission, which is both motor-reducer-driven and [...] Read more.
Unlike the conventional robotic arm where the joints are coupled to each other, this paper proposes a position and posture decoupling method to mechanically correct the end position of the robotic arm in real time through dual-motion transmission, which is both motor-reducer-driven and chain-driven; when the position of the end of the robotic arm changes, the positional linkage of each articulated arm end is unaffected. First, a single-section chain-driven decoupled robotic arm is constructed, and then the design of a two-degrees-of-freedom chain-driven decoupled robotic arm system is completed based on a single arm. Second, kinematic analysis of the decoupled robotic arm system is performed to obtain its trajectory and workspace. Moreover, an analysis of the transmission mechanism engagement clearance error is carried out. Finally, a mini-experimental prototype is built, and the rationality of the decoupled robotic arm system is proven by experiments. The experimental results show that the robotic arm is generally able to realize positional decoupling stably during movement, providing certain theoretical support and practical experience for the design requirements of related robotic arms. Full article
(This article belongs to the Section Machine Design and Theory)
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15 pages, 1924 KiB  
Article
Parameter Identification of Flexible Link Manipulators Using Evolutionary Algorithms
by Fabian Andres Lara-Molina
Machines 2024, 12(6), 409; https://doi.org/10.3390/machines12060409 - 14 Jun 2024
Viewed by 986
Abstract
This paper addresses the parameter identification of a one-link flexible manipulator based on the experimental measurement of the inputs/outputs, the finite element model, and the application of evolutionary algorithms. A novel approach is proposed to find the values of inertia, stiffness, and damping [...] Read more.
This paper addresses the parameter identification of a one-link flexible manipulator based on the experimental measurement of the inputs/outputs, the finite element model, and the application of evolutionary algorithms. A novel approach is proposed to find the values of inertia, stiffness, and damping parameters by minimizing the difference between the numerical model’s outputs and the testbed’s outputs, thus considering the joint position and acceleration of the link’s tip. The dynamic model is initially obtained using the finite element method and the Lagrange principle. A prototype of a single one-link flexible manipulator is used in the experimental application, wherein the servomotor applies the input torque, and the outputs are the joint angle and the link’s tip acceleration. Then, an optimization problem minimizes the difference between the numerical and experimental outputs to determine the set of parameters using evolutionary algorithms. A comparative analysis to obtain the identified parameters is established using genetic algorithms, particle swarm optimization, and differential evolution. The proposed identification approach permitted the determination of the dynamic parameters based on the complete dynamic model of the flexible-link manipulator, which is different from the approaches reported in the literature that identify a simplified model. This information is essential for the design of the motion and vibration control laws. Full article
(This article belongs to the Special Issue Nonlinear Mechanical Vibration in Machine Design)
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18 pages, 6836 KiB  
Article
Advanced Waterjet Technology for Machining Beveled Structures of High-Strength and Thick Material
by Mingming Du, Wei Zhong, Zhichao Song, Jialin Teng, Wei Liang and Haijin Wang
Machines 2024, 12(6), 408; https://doi.org/10.3390/machines12060408 - 13 Jun 2024
Viewed by 1170
Abstract
The bevel cutting of large-thickness plates is a key process in modern industries. However, traditional processing method such as air-arc gouging bevel cutting or laser bevel cutting may cause serious deformation and rough surface quality due to the defects of the thermal cutting [...] Read more.
The bevel cutting of large-thickness plates is a key process in modern industries. However, traditional processing method such as air-arc gouging bevel cutting or laser bevel cutting may cause serious deformation and rough surface quality due to the defects of the thermal cutting method. In order to improve the quality and efficiency of bevel processing, the abrasive waterjet cutting method is used in this research to overcome the challenge for bevel machining of high-strength DH40 steel plates with a large thickness. For different kinds of beveled structures, a 3D camera is used to measure the reference points defined on the workpiece and the SVD registration algorithm is adopted to transform the theoretical coordinate system to the actual coordinate system. Furthermore, the distance between the nozzle and the workpiece surface is also measured and compensated for to ensure the consistency of the bevel width. Finally, experiments are carried out for different kinds of bevels to verify the feasibility of the proposed method for high precision processing for beveled structures. The developed method has been effectively applied in the actual shipbuilding industry. Full article
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25 pages, 2972 KiB  
Article
Maintainability Analysis of Remotely Operated LNG Marine Loading Arms Based on UNE 151001 Standard
by Fabian Orellana, Orlando Durán, José Ignacio Vergara and Adolfo Arata
Machines 2024, 12(6), 407; https://doi.org/10.3390/machines12060407 - 13 Jun 2024
Viewed by 855
Abstract
The operation of liquefied natural gas (LNG) marine loading arms plays a pivotal role in the efficient transfer of LNG from maritime vessels to downstream facilities, underpinning the global LNG supply chain. Despite their criticality, these systems frequently encounter operational challenges, notably slow [...] Read more.
The operation of liquefied natural gas (LNG) marine loading arms plays a pivotal role in the efficient transfer of LNG from maritime vessels to downstream facilities, underpinning the global LNG supply chain. Despite their criticality, these systems frequently encounter operational challenges, notably slow coupling speeds and increased downtimes driven by maintenance demands. Addressing these challenges, Physical Asset Management principles advocate for maximizing process availability by minimizing both planned and unplanned outages. Recognizing maintainability as a key equipment attribute, this document proposes a procedure that extends the use of the UNE 151001 standard to evaluate the maintainability of physical assets. This proposal incorporates into traditional RCM a step for the selection of maintenance levels proposed in the standard, as well as the use of the AHP technique for selecting the weights used during the analysis process. Finally, an aggregated maintainability indicator is presented, which will allow for better evaluation, comparison, and monitoring of this characteristic in one or more industrial assets. To demonstrate its feasibility and utility, the proposed procedure is applied to a set of LNG marine unloading arms. This study identifies pivotal areas for improvement and devises strategic action plans aimed at enhancing asset’s maintainability. The outcomes of this analysis not only provide a roadmap for augmenting operational efficiency but also furnish empirical justification for the requisite investments in maintainability enhancements, thereby contributing to the resilience and sustainability of LNG logistics infrastructure. Full article
(This article belongs to the Section Machines Testing and Maintenance)
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16 pages, 2697 KiB  
Article
Kinematic Parameter Identification and Error Compensation of Industrial Robots Based on Unscented Kalman Filter with Adaptive Process Noise Covariance
by Guanbin Gao, Xinyang Guo, Gengen Li, Yuan Li and Houchen Zhou
Machines 2024, 12(6), 406; https://doi.org/10.3390/machines12060406 - 12 Jun 2024
Viewed by 1132
Abstract
Kinematic calibration plays a pivotal role in enhancing the absolute positioning accuracy of industrial robots, with parameter identification and error compensation constituting its core components. While the conventional parameter identification method, based on linearization, has shown promise, it suffers from the loss of [...] Read more.
Kinematic calibration plays a pivotal role in enhancing the absolute positioning accuracy of industrial robots, with parameter identification and error compensation constituting its core components. While the conventional parameter identification method, based on linearization, has shown promise, it suffers from the loss of high-order system information. To address this issue, we propose an unscented Kalman filter (UKF) with adaptive process noise covariance for robot kinematic parameter identification. The kinematic model of a typical 6-degree-of-freedom industrial robot is established. The UKF is introduced to identify the unknown constant parameters within this model. To mitigate the reliance of the UKF on the process noise covariance, an adaptive process noise covariance strategy is proposed to adjust and correct this covariance. The effectiveness of the proposed algorithm is then demonstrated through identification and error compensation experiments for the industrial robot. Results indicate its superior stability and accuracy across various initial conditions. Compared to the conventional UKF algorithm, the proposed approach enhances the robot’s accuracy stability by 25% under differing initial conditions. Moreover, compared to alternative methods such as the extended Kalman algorithm, particle swarm optimization algorithm, and grey wolf algorithm, the proposed approach yields average improvements of 4.13%, 26.47%, and 41.59%, respectively. Full article
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16 pages, 4414 KiB  
Article
Experimental Evaluation of Flexible Fixture Stiffness for Steering Knuckles When Loading a Milling Machine Tool
by Vitalii Kolesnyk, Marcel Kuruc, Ivan Dehtiarov, Anna Neshta, Serhii Avramenko, Vitalii Kononovych, Oksana Dynnyk, Andrii Dovhopolov, Serhii Lemekh and Roman Titskyi
Machines 2024, 12(6), 405; https://doi.org/10.3390/machines12060405 - 12 Jun 2024
Viewed by 1054
Abstract
In the conditions of the increase in the range of products in the automobile and aircraft industry, there is a tendency to increase the scope of application of flexible fixtures. Thus, in the current article, it was proposed to consider a new concept [...] Read more.
In the conditions of the increase in the range of products in the automobile and aircraft industry, there is a tendency to increase the scope of application of flexible fixtures. Thus, in the current article, it was proposed to consider a new concept of a flexible fixture for location parts of a complex shape. The stress and deflection of the steering knuckle elements were calculated using finite element modeling. During the experiment on the static loading, the deflection of the steering knuckle elements was measured, and the results of finite element modeling were validated. It was determined that the stiffness of the proposed flexible fixture ensures compliance with the tolerances of the mutual location of the surfaces of the part, making it reasonable for feature research the novel flexible fixture design during milling. Full article
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20 pages, 11034 KiB  
Article
Experimental Evaluation of Mechanical Compression Properties of Aluminum Alloy Lattice Trusses for Anti-Ice System Applications
by Carlo Giovanni Ferro, Sara Varetti and Paolo Maggiore
Machines 2024, 12(6), 404; https://doi.org/10.3390/machines12060404 - 12 Jun 2024
Viewed by 923
Abstract
Lattice structures have emerged as promising materials for aerospace structure applications due to their high strength-to-weight ratios, customizable properties, and efficient use of materials. These properties make them attractive for use in anti-ice systems, where lightweight and heat exchange are essential. This paper [...] Read more.
Lattice structures have emerged as promising materials for aerospace structure applications due to their high strength-to-weight ratios, customizable properties, and efficient use of materials. These properties make them attractive for use in anti-ice systems, where lightweight and heat exchange are essential. This paper presents an extensive experimental investigation into mechanical compression properties of lattice trusses fabricated from AlSi10Mg powder alloy, a material commonly used in casted aerospace parts. The truss structures were manufactured using the additive manufacturing selective laser melting technique and were subjected to uniaxial compressive loading to assess their performance. The results demonstrate that AlSi10Mg lattice trusses exhibit remarkable compressive strength with strong correlations depending upon both topology and cells’ parameters setup. The findings described highlight the potential of AlSi10Mg alloy as a promising material for custom truss fabrication, offering customizable cost-effective and lightweight solutions for the aerospace market. This study also emphasizes the role of additive manufacturing in producing complex structures with pointwise-tailored mechanical properties. Full article
(This article belongs to the Special Issue Recent Advances in 3D Printing in Industry 4.0)
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27 pages, 11125 KiB  
Article
Advancing Predictive Maintenance with PHM-ML Modeling: Optimal Covariate Weight Estimation and State Band Definition under Multi-Condition Scenarios
by David R. Godoy, Constantino Mavrakis, Rodrigo Mena, Fredy Kristjanpoller and Pablo Viveros
Machines 2024, 12(6), 403; https://doi.org/10.3390/machines12060403 - 12 Jun 2024
Cited by 1 | Viewed by 1076
Abstract
The proportional hazards model (PHM) is a vital statistical procedure for condition-based maintenance that integrates age and covariates monitoring to estimate asset health and predict failure risks. However, when dealing with multi-covariate scenarios, the PHM faces interpretability challenges when it lacks coherent criteria [...] Read more.
The proportional hazards model (PHM) is a vital statistical procedure for condition-based maintenance that integrates age and covariates monitoring to estimate asset health and predict failure risks. However, when dealing with multi-covariate scenarios, the PHM faces interpretability challenges when it lacks coherent criteria for defining each covariate’s influence degree on the hazard rate. Hence, we proposed a comprehensive machine learning (ML) formulation with Interior Point Optimizer and gradient boosting to maximize and converge the logarithmic likelihood for estimating covariate weights, and a K-means and Gaussian mixture model (GMM) for condition state bands. Using real industrial data, this paper evaluates both clustering techniques to determine their suitability regarding reliability, remaining useful life, and asset intervention decision rules. By developing models differing in the selected covariates, the results show that although K-means and GMM produce comparable policies, GMM stands out for its robustness in cluster definition and intuitive interpretation in generating the state bands. Ultimately, as the evaluated models suggest similar policies, the novel PHM-ML demonstrates the robustness of its covariate weight estimation process, thereby strengthening the guidance for predictive maintenance decisions. Full article
(This article belongs to the Section Machines Testing and Maintenance)
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40 pages, 4940 KiB  
Review
A Review on the Applications of Dual Quaternions
by João Gutemberg Farias, Edson De Pieri and Daniel Martins
Machines 2024, 12(6), 402; https://doi.org/10.3390/machines12060402 - 12 Jun 2024
Viewed by 1883
Abstract
This work explores dual quaternions and their applications. First, a theoretical construction begins at dual numbers, extends to dual vectors, and culminates in dual quaternions. The physical foundations behind the developed theory lie in two important fundamentals: Chasles’ Theorem and the Transference Principle. [...] Read more.
This work explores dual quaternions and their applications. First, a theoretical construction begins at dual numbers, extends to dual vectors, and culminates in dual quaternions. The physical foundations behind the developed theory lie in two important fundamentals: Chasles’ Theorem and the Transference Principle. The former addresses how to represent rigid-body motion whereas the latter provides a method for operating on it. This combination presents dual quaternions as a framework for modeling rigid mechanical systems, both kinematically and kinetically, in a compact, elegant and performant way. Next, a review on the applications of dual quaternions is carried out, providing a general overview of all applications. Important subjects are further detailed, these being the kinematics and dynamics of rigid bodies and mechanisms (both serial and parallel), control and motion interpolation. Discussions regarding dual quaternions and their applications are undertaken, highlighting open questions and research gaps. The advantages and disadvantages of using dual quaternions are summarized. Lastly, conclusions and future directions of research are presented. Full article
(This article belongs to the Special Issue Control and Mechanical System Engineering)
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20 pages, 7948 KiB  
Article
Comparative Study of Short Circuits and Demagnetization in Delta, Star, and Hybrid Winding Connections for Surface-Mounted Permanent Magnet Machines
by Junyi Chen, Yidong Du, Haolan Zhan, Kai Zhou and Yuan Sun
Machines 2024, 12(6), 401; https://doi.org/10.3390/machines12060401 - 12 Jun 2024
Viewed by 1105
Abstract
This article comprehensively compares the short circuits and irreversible demagnetization in star, delta, and hybrid winding connections for surface-mounted permanent magnet (SPM) machines, including the three-phase short circuit (3PSC) and two-phase short circuit (2PSC). The analytical and finite element (FE) methods are adopted. [...] Read more.
This article comprehensively compares the short circuits and irreversible demagnetization in star, delta, and hybrid winding connections for surface-mounted permanent magnet (SPM) machines, including the three-phase short circuit (3PSC) and two-phase short circuit (2PSC). The analytical and finite element (FE) methods are adopted. It is found that when 3PSC or 2PSC happens, the peak current is the largest in the hybrid connection, which further results in the severest demagnetization. In addition, the delta connection always results in a larger 2PSC peak current than the star connection. Under relatively low permanent magnet (PM) temperature, the delta connection leads to more severe demagnetization than the star connection. However, when PM temperature increases, the opposite condition can occur. As for 3PSC, whether the peak current of the delta connection exceeds that of the star connection is determined by the phase of the third back-EMF harmonic. The delta connection shows higher 3PSC peak current when the third harmonic is in phase with the fundamental back EMF, and conversely, the star connection shows higher peak current. The comparison of demagnetization also heavily depends on PM temperature. Finally, the experiments are conducted to verify the theoretical analysis. Full article
(This article belongs to the Section Electrical Machines and Drives)
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22 pages, 12361 KiB  
Article
Design and Experimental Study of Negative Pressure Spiral Separation and Reduction Device for Drilling Holes
by Xiangang Ren, Yongchen Huang, Bo Zhang and Zhuo Wang
Machines 2024, 12(6), 400; https://doi.org/10.3390/machines12060400 - 12 Jun 2024
Viewed by 755
Abstract
Currently, screw conveyors and negative pressure vacuum screens with negative pressure vibration units are used for handling drilling cuttings both domestically and internationally. However, there is currently no effective solution to address the high liquid content of drilling cuttings during their conveyance by [...] Read more.
Currently, screw conveyors and negative pressure vacuum screens with negative pressure vibration units are used for handling drilling cuttings both domestically and internationally. However, there is currently no effective solution to address the high liquid content of drilling cuttings during their conveyance by screw conveyors. In this paper, a novel design scheme for a negative pressure spiral separation and reduction device is proposed based on an extensive literature survey. This device aims to effectively reduce the liquid content of drilling cuttings during their conveyance by screw conveyors, thereby minimizing the overall liquid content throughout the drilling process. The structural design of the negative pressure spiral separation and reduction device is conducted using theoretical analysis and 3D solid modeling methods, while strength analysis of the negative pressure suction unit is performed using a finite element method. Additionally, theoretical research on relevant process parameters is carried out, and an online real-time testing system for experiments is designed. An analysis of experimental results demonstrates that within 151 s, the liquid suction rate of the device can reach 51%, with an average flow speed of approximately 0.008 m/s, thus achieving the desired target for drilling cutting separation and reduction. By designing this new negative pressure spiral separation and reduction device, its feasibility has been verified through acceptable engineering results obtained from experimentation; furthermore, it aims to achieve an optimal liquid suction effect for drilling cuttings in order to enhance solid–liquid separation efficiency, as well as to improve drilling fluid recovery efficiency by conserving mud materials and reducing overall drilling costs. Full article
(This article belongs to the Section Machine Design and Theory)
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20 pages, 8172 KiB  
Article
Incipient Inter-Turn Short Circuit Detection in Induction Motors Using Cumulative Distribution Function and the EfficientNetv2 Model
by Carlos Javier Morales-Perez, Laritza Perez-Enriquez, Juan Pablo Amezquita-Sanchez, Jose de Jesus Rangel-Magdaleno, Martin Valtierra-Rodriguez and David Granados-Lieberman
Machines 2024, 12(6), 399; https://doi.org/10.3390/machines12060399 - 12 Jun 2024
Viewed by 1019
Abstract
Induction motors are one of the most used machines because they provide the necessary traction force for many industrial applications. Their easy operation, installation, maintenance, and reliability make them preferred over other electrical motors. Mechanical and electrical failures, as with other machines, can [...] Read more.
Induction motors are one of the most used machines because they provide the necessary traction force for many industrial applications. Their easy operation, installation, maintenance, and reliability make them preferred over other electrical motors. Mechanical and electrical failures, as with other machines, can appear at any stage of their service life, making the stator intern-turn short-circuit fault (ITSC) stand out. Hence, its detection is necessary in order to extend and save useful life, avoiding a breakdown and unprogrammed maintenance processes as well as, in the worst circumstances, a total loss of the machine. Nonetheless, the challenge lies in detecting this type of fault, which has made the analysis and diagnosis processes easier. Such is the case with convolutional neural networks (CNNs), which facilitate the development of methodologies for pattern recognition in several areas of knowledge. Unfortunately, these techniques require a large amount of data for an adequate training process, which is not always available. In this sense, this paper presents a new methodology for the detection of incipient ITSC faults employing a modified cumulative distribution function (CDF) of the current stator signal. Then, these are converted to images and fed into a fast and compact CNN model, trained with a small data set, reaching up to 99.16% accuracy for seven conditions (0, 5, 10, 15, 20, 30, and 40 short-circuited turns) and four mechanical load conditions. Full article
(This article belongs to the Special Issue Data-Driven Fault Diagnosis for Machines and Systems)
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16 pages, 6124 KiB  
Article
Structural Optimization of Scarfing Machine with Acceleration Profile and Multi-Objective Genetic Algorithm Approach
by Sangbin Lee, Yoonjae Lee, Byeonghui Park and Changwoo Lee
Machines 2024, 12(6), 398; https://doi.org/10.3390/machines12060398 - 12 Jun 2024
Cited by 1 | Viewed by 1058
Abstract
Scarfing is a type of flame treatment used to improve the quality of metal generated during steelmaking. It employs the principles of gas cutting to remove impurities and defects. Due to the high-temperature conditions and the need for uniform metal treatment, mechanical scarfing [...] Read more.
Scarfing is a type of flame treatment used to improve the quality of metal generated during steelmaking. It employs the principles of gas cutting to remove impurities and defects. Due to the high-temperature conditions and the need for uniform metal treatment, mechanical scarfing performed via a frame is preferred over manual hand scarfing. To achieve stable mechanical scarfing, a properly designed frame is essential. Generally, while using more material can create stable equipment, it also increases costs. Therefore, this study proposed a design method that selects an acceleration profile to minimize the shock on the frame during scarfing equipment operation while using a multi-objective genetic algorithm to minimize weight and maximize rigidity. Because modifying existing scarfing equipment based on the optimization results would incur additional costs and time, pre-optimizing through simulation before equipment fabrication is crucial. Optimization was achieved via the dimensional optimization of the existing frame equipment. As a result, the weight of each part and the deformation decreased by an average of 17.05 kg and 3.93%, respectively. Full article
(This article belongs to the Special Issue Optimization and Design of Compliant Mechanisms)
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18 pages, 7970 KiB  
Article
Defining the Consistent Velocity of Omnidirectional Mobile Platforms
by Elena Rubies and Jordi Palacín
Machines 2024, 12(6), 397; https://doi.org/10.3390/machines12060397 - 11 Jun 2024
Cited by 1 | Viewed by 966
Abstract
The maximum linear (or translational) velocity achievable by an omnidirectional platform is not uniform as it depends on the angular orientation of the motion. This velocity is limited by the maximum angular velocity of the motors driving the wheels and also depends on [...] Read more.
The maximum linear (or translational) velocity achievable by an omnidirectional platform is not uniform as it depends on the angular orientation of the motion. This velocity is limited by the maximum angular velocity of the motors driving the wheels and also depends on the mechanical configuration and orientation of the wheels. This paper proposes a procedure to compute an upper bound for the translational velocity, named the consistent velocity of the omnidirectional platform, which is defined as the minimum of the maximum translational velocities achievable by the platform in any angular orientation with no wheel slippage. The consistent velocity is then a uniform translational velocity always achievable by the omnidirectional platform regardless of the angular orientation of the motion. This paper reports the consistent velocity for a set of omnidirectional platforms with three omni wheels that have the same radius and angular distribution but different angular orientations. Results have shown that these platforms can achieve different maximum velocities in different angular orientations although the consistent velocity is the same for all of them. Results have also shown that the consistent velocity has a linear relation with the angular velocity of the motion. The consistent velocity of a mobile platform can be used by its path-planning algorithm as an upper bound that guarantees the execution of any omnidirectional motion at a uniform and maximum translational velocity. Full article
(This article belongs to the Special Issue Recent Advances in Mobile Robots)
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