Pub Date : 2024-07-24DOI: 10.1177/16878132241263506
Xuejing Du, Zhenzhen Chen, Jiali Song, Zhanyu Wang
The joints in an automobile’s body structure are crucial in bearing loads and transmitting stresses, thereby significantly affecting the body’s rigidity. To effectively improve body rigidity and crashworthiness, this study employed a sensitivity analysis to identify the critical joints among the nine joints of a specific sport utility vehicle (SUV) body. Following regulatory requirements, collision simulations were performed, revealing that the joint below the B-pillar exhibited the most significant deformation. Thus, using the material and thickness of the B-pillar’s lower joint as design variables, experimental samples were generated by the design of experiment (DOE). A multi-objective optimization for the B-pillar’s lower joint model was conducted using the response surface method and the simulated annealing algorithm to determine the final optimized solution. The optimization results showed a 9.31% increase in body bending stiffness, an 11.37% increase in torsional stiffness, and reduced intrusion at various points on the B-pillar, effectively enhancing the body’s rigidity and crashworthiness.
汽车车身结构中的关节是承受载荷和传递应力的关键，因此会对车身刚度产生重大影响。为了有效提高车身刚度和耐撞性，本研究采用了敏感性分析方法来确定特定运动型多用途车（SUV）车身九个关节中的关键关节。根据法规要求，进行了碰撞模拟，结果表明 B 柱下方的接合处变形最大。因此，以 B 柱下连接处的材料和厚度为设计变量，通过实验设计（DOE）生成了实验样本。采用响应面法和模拟退火算法对 B 柱下接缝模型进行了多目标优化，以确定最终优化方案。优化结果表明，车身弯曲刚度提高了 9.31%，扭转刚度提高了 11.37%，B 柱各点的侵入量减少，有效提高了车身刚度和耐撞性。
{"title":"Multi-objective optimization of vehicle body B-pillar lower joints based on crashworthiness analysis","authors":"Xuejing Du, Zhenzhen Chen, Jiali Song, Zhanyu Wang","doi":"10.1177/16878132241263506","DOIUrl":"https://doi.org/10.1177/16878132241263506","url":null,"abstract":"The joints in an automobile’s body structure are crucial in bearing loads and transmitting stresses, thereby significantly affecting the body’s rigidity. To effectively improve body rigidity and crashworthiness, this study employed a sensitivity analysis to identify the critical joints among the nine joints of a specific sport utility vehicle (SUV) body. Following regulatory requirements, collision simulations were performed, revealing that the joint below the B-pillar exhibited the most significant deformation. Thus, using the material and thickness of the B-pillar’s lower joint as design variables, experimental samples were generated by the design of experiment (DOE). A multi-objective optimization for the B-pillar’s lower joint model was conducted using the response surface method and the simulated annealing algorithm to determine the final optimized solution. The optimization results showed a 9.31% increase in body bending stiffness, an 11.37% increase in torsional stiffness, and reduced intrusion at various points on the B-pillar, effectively enhancing the body’s rigidity and crashworthiness.","PeriodicalId":7357,"journal":{"name":"Advances in Mechanical Engineering","volume":"82 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141780694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1177/16878132241265830
Xinhua Zhao, Shangze Chen, Kang Wang
During the longitudinal motion of a supercavitating vehicle, the stability control problem is complicated because of the nonlinear planing force on the tail part. The dynamic model of a supercavitating vehicle in longitude plane is nonlinear, simultaneously, the control instructions of a supercavitating vehicle may exceed the physical limits of an actuator. Therefore, designing a longitudinal stability control system for a supercavitating vehicle, not only the treatment of nonlinear planing force, but also the physical constraints of the actuator should be considered. For the longitudinal motion model of supercavitating vehicle, a cascade model is proposed, which decomposes the longitudinal motion of supercavitating vehicle into two subsystems. Sliding mode control based on RBF neural network compensation is adopted in the controller design process, and RBF neural network is exploited to approach the deviation caused by actuator saturation. The proposed control method can effectively compensate the performance degradation caused by control variable saturation, and has strong robustness.
{"title":"Anti-windup design for supercavitating vehicle based on sliding mode control combined with RBF network","authors":"Xinhua Zhao, Shangze Chen, Kang Wang","doi":"10.1177/16878132241265830","DOIUrl":"https://doi.org/10.1177/16878132241265830","url":null,"abstract":"During the longitudinal motion of a supercavitating vehicle, the stability control problem is complicated because of the nonlinear planing force on the tail part. The dynamic model of a supercavitating vehicle in longitude plane is nonlinear, simultaneously, the control instructions of a supercavitating vehicle may exceed the physical limits of an actuator. Therefore, designing a longitudinal stability control system for a supercavitating vehicle, not only the treatment of nonlinear planing force, but also the physical constraints of the actuator should be considered. For the longitudinal motion model of supercavitating vehicle, a cascade model is proposed, which decomposes the longitudinal motion of supercavitating vehicle into two subsystems. Sliding mode control based on RBF neural network compensation is adopted in the controller design process, and RBF neural network is exploited to approach the deviation caused by actuator saturation. The proposed control method can effectively compensate the performance degradation caused by control variable saturation, and has strong robustness.","PeriodicalId":7357,"journal":{"name":"Advances in Mechanical Engineering","volume":"82 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141780745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1177/16878132241264944
Pan Lu, Zhang Chen-lin, Liu Tong, Wang Liang, Zhang Heng-hua
Laser Powder Bed Fusion (LPBF) is a promising metal additive manufacturing technology based on layer by layer powder spreading, and powder bed uniformity has a great influence on the forming quality. By Discrete Element Method and powder spreading experiment, the interaction and movement between powder were studied during powder spreading, including powder jamming, rebound, splash, eddy, and empty powder area. Additionally, five kinds of powder spreading schemes were explored, and the new process of one-way reciprocating with tri-splint blade was designed to change the motion state of powder spreading from “blade pushing powder” to “blade holding powder.” By increasing the distance between the blade and the working platform form 0 to 20 µm with the distance between the upper surface of the substrate and the working platform 50 µm, defects such as powder splash and empty powder decreased. And the uniform powder bed of aluminum alloy powder was achieved with the new process of one-way reciprocating with tri-splint blade structure.
{"title":"Powder movement rules of laser powder bed fusion additive manufacturing aluminum alloy based on discrete element method","authors":"Pan Lu, Zhang Chen-lin, Liu Tong, Wang Liang, Zhang Heng-hua","doi":"10.1177/16878132241264944","DOIUrl":"https://doi.org/10.1177/16878132241264944","url":null,"abstract":"Laser Powder Bed Fusion (LPBF) is a promising metal additive manufacturing technology based on layer by layer powder spreading, and powder bed uniformity has a great influence on the forming quality. By Discrete Element Method and powder spreading experiment, the interaction and movement between powder were studied during powder spreading, including powder jamming, rebound, splash, eddy, and empty powder area. Additionally, five kinds of powder spreading schemes were explored, and the new process of one-way reciprocating with tri-splint blade was designed to change the motion state of powder spreading from “blade pushing powder” to “blade holding powder.” By increasing the distance between the blade and the working platform form 0 to 20 µm with the distance between the upper surface of the substrate and the working platform 50 µm, defects such as powder splash and empty powder decreased. And the uniform powder bed of aluminum alloy powder was achieved with the new process of one-way reciprocating with tri-splint blade structure.","PeriodicalId":7357,"journal":{"name":"Advances in Mechanical Engineering","volume":"7 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141780743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1177/16878132241262580
Jingyun Xue, Xuebin Liu, Hanshan Li
With the widespread application and development of unmanned aerial vehicle (UAV) technology, ensuring the security and stability of UAV swarm communication networks has become crucial. Given the diverse forms of interference and attacks in current networks, this poses a serious threat to the normal operation of UAV swarm communication. Therefore, how to accurately identify and effectively counter these network threats has become the focus of research. This study comprehensively evaluates the core technology of UAV swarm communication network situational awareness and constructs a situational awareness model based on adversarial networks. The model utilizes adversarial network technology and combines data collection and processing to design four experiments to comprehensively evaluate the performance of the model in different scenarios. The experimental results show that as the amount of data gradually increases, the performance of the model also improves. When processing 100, 1000, and 10,000 data points, the model achieved accuracies of 0.955, 0.962, and 0.982, respectively. Furthermore, the experimental results also indicate that effective noise suppression measures can significantly improve the accuracy and stability of the situational awareness model. Additionally, it is noted that different model structures will affect training duration, accuracy, and stability. Although increasing network scale may lead to increased computational complexity and latency, its accuracy is correspondingly improved. The adversarial network-based situational awareness model proposed in this study can accurately identify and effectively counter interference and attacks in UAV swarm communication networks, thereby providing solid protection for the collaborative combat and information sharing of UAV swarms.
{"title":"Investigation on situation awareness model of unmanned aerial vehicle groups communication network based on adversarial network","authors":"Jingyun Xue, Xuebin Liu, Hanshan Li","doi":"10.1177/16878132241262580","DOIUrl":"https://doi.org/10.1177/16878132241262580","url":null,"abstract":"With the widespread application and development of unmanned aerial vehicle (UAV) technology, ensuring the security and stability of UAV swarm communication networks has become crucial. Given the diverse forms of interference and attacks in current networks, this poses a serious threat to the normal operation of UAV swarm communication. Therefore, how to accurately identify and effectively counter these network threats has become the focus of research. This study comprehensively evaluates the core technology of UAV swarm communication network situational awareness and constructs a situational awareness model based on adversarial networks. The model utilizes adversarial network technology and combines data collection and processing to design four experiments to comprehensively evaluate the performance of the model in different scenarios. The experimental results show that as the amount of data gradually increases, the performance of the model also improves. When processing 100, 1000, and 10,000 data points, the model achieved accuracies of 0.955, 0.962, and 0.982, respectively. Furthermore, the experimental results also indicate that effective noise suppression measures can significantly improve the accuracy and stability of the situational awareness model. Additionally, it is noted that different model structures will affect training duration, accuracy, and stability. Although increasing network scale may lead to increased computational complexity and latency, its accuracy is correspondingly improved. The adversarial network-based situational awareness model proposed in this study can accurately identify and effectively counter interference and attacks in UAV swarm communication networks, thereby providing solid protection for the collaborative combat and information sharing of UAV swarms.","PeriodicalId":7357,"journal":{"name":"Advances in Mechanical Engineering","volume":"245 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141780598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1177/16878132241263471
Hamzeh Duwairi, Nesreen Sukkar, Mohammad Alrbai
This paper investigates the effect of corrugated surfaces on the wind turbines power output for both laminar and turbulent flows. Conservation principles including continuity and momentum equations, wind turbine power equations, and the corrugated surface equation have been implemented to build up a theoretical model then which has been solved using MATLAB. This model simulates wind turbines power output and analyzes several case studies implementing different parameters such as air pressure wave amplitude (Po), air wave fluctuation frequency (n), and wind layer turbulence (b). Also, different complex terrains in two main scenarios representing two different positions (X) of the wind turbine are analyzed. This analysis indicates the importance of wind turbines micro siting. In addition, it is found that increasing the pressure ratio increased wind turbine power output, while increasing the frequency decreased the power ratio of the wind turbines for both laminar and turbulent flow conditions. Increasing turbulence for the turbulent model increased the power ratio.
{"title":"Fluctuating pressure gradients and corrugated surfaces effects on wind turbines power output","authors":"Hamzeh Duwairi, Nesreen Sukkar, Mohammad Alrbai","doi":"10.1177/16878132241263471","DOIUrl":"https://doi.org/10.1177/16878132241263471","url":null,"abstract":"This paper investigates the effect of corrugated surfaces on the wind turbines power output for both laminar and turbulent flows. Conservation principles including continuity and momentum equations, wind turbine power equations, and the corrugated surface equation have been implemented to build up a theoretical model then which has been solved using MATLAB. This model simulates wind turbines power output and analyzes several case studies implementing different parameters such as air pressure wave amplitude (P<jats:sub>o</jats:sub>), air wave fluctuation frequency (n), and wind layer turbulence (b). Also, different complex terrains in two main scenarios representing two different positions (X) of the wind turbine are analyzed. This analysis indicates the importance of wind turbines micro siting. In addition, it is found that increasing the pressure ratio increased wind turbine power output, while increasing the frequency decreased the power ratio of the wind turbines for both laminar and turbulent flow conditions. Increasing turbulence for the turbulent model increased the power ratio.","PeriodicalId":7357,"journal":{"name":"Advances in Mechanical Engineering","volume":"37 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141780776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1177/16878132241264410
Liqun Huangfu, Chen Cen, Tao Zhang
In this paper, the model predictive current control (MPCC) is proposed to reduce the torque ripple of a switched reluctance motor by realizing precise current tracking. The Linear Quadratic Regulator (LQR) is employed to establish the cost functions of MPCC, which can select optimal control variables. Besides, the Kalman filter is employed to estimate the system state to reduce the influence of disturbance. In addition, the PI controller is replaced by automatic disturbance rejection control (ADRC) to further improve the robustness of the system. Finally, experimental results are shown to verify the effectiveness regarding distinguished tracking performance, dynamic response, and robustness of the proposed MPCC. It can be found that the improved MPCC proposed in this paper can achieve lower torque ripple, distinguished current tracking performance, and dynamic response performance.
本文提出了模型预测电流控制（MPCC），通过实现精确的电流跟踪来降低开关磁阻电机的转矩纹波。采用线性二次调节器（LQR）建立 MPCC 的成本函数，从而选择最佳控制变量。此外，还采用卡尔曼滤波器来估计系统状态，以减少干扰的影响。此外，自动干扰抑制控制（ADRC）取代了 PI 控制器，进一步提高了系统的鲁棒性。最后，实验结果验证了所提出的 MPCC 在卓越的跟踪性能、动态响应和鲁棒性方面的有效性。实验结果表明，本文提出的改进型 MPCC 可以实现更低的扭矩纹波、出色的电流跟踪性能和动态响应性能。
{"title":"A modified model predictive current control of SRMs for torque ripple suppression","authors":"Liqun Huangfu, Chen Cen, Tao Zhang","doi":"10.1177/16878132241264410","DOIUrl":"https://doi.org/10.1177/16878132241264410","url":null,"abstract":"In this paper, the model predictive current control (MPCC) is proposed to reduce the torque ripple of a switched reluctance motor by realizing precise current tracking. The Linear Quadratic Regulator (LQR) is employed to establish the cost functions of MPCC, which can select optimal control variables. Besides, the Kalman filter is employed to estimate the system state to reduce the influence of disturbance. In addition, the PI controller is replaced by automatic disturbance rejection control (ADRC) to further improve the robustness of the system. Finally, experimental results are shown to verify the effectiveness regarding distinguished tracking performance, dynamic response, and robustness of the proposed MPCC. It can be found that the improved MPCC proposed in this paper can achieve lower torque ripple, distinguished current tracking performance, and dynamic response performance.","PeriodicalId":7357,"journal":{"name":"Advances in Mechanical Engineering","volume":"35 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141780749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1177/16878132241266536
Aiman Albatayneh
The rise of electric vehicles (EVs) is undoubtedly revolutionizing the automotive industry, and its impact on the car repair and service business is profound. While exciting opportunities emerge, the shift also presents significant challenges, potentially leading to the disappearance of certain jobs and parts. In this research, we explore the impact of electric cars on the future car repair and service landscape. By 2030, EVs will constitute 60% of global car sales, underscoring the significant shift towards electric mobility. This transition is expected to reduce maintenance costs by up to 40% compared to conventional vehicles due to the simpler design and fewer moving parts in EVs. Certain body parts, including radiators and exhaust systems specific to gasoline cars, will also become redundant as EVs become more prevalent in the market. However, amidst these disappearing parts, there are emerging opportunities in the automotive industry. The rise of EVs will necessitate new areas of expertise, such as battery diagnostics, charging infrastructure installation, and software updates, creating new job opportunities for trained technicians. Furthermore, there will be a growing focus on software and electronics as they play a bigger role in car functionality. This shift emphasizes the importance of upskilling existing technicians in these areas to capitalize on new avenues within the automotive sector, aligning with the evolving landscape of electric mobility.
{"title":"The electric cars era transforming the car repairs and services landscape","authors":"Aiman Albatayneh","doi":"10.1177/16878132241266536","DOIUrl":"https://doi.org/10.1177/16878132241266536","url":null,"abstract":"The rise of electric vehicles (EVs) is undoubtedly revolutionizing the automotive industry, and its impact on the car repair and service business is profound. While exciting opportunities emerge, the shift also presents significant challenges, potentially leading to the disappearance of certain jobs and parts. In this research, we explore the impact of electric cars on the future car repair and service landscape. By 2030, EVs will constitute 60% of global car sales, underscoring the significant shift towards electric mobility. This transition is expected to reduce maintenance costs by up to 40% compared to conventional vehicles due to the simpler design and fewer moving parts in EVs. Certain body parts, including radiators and exhaust systems specific to gasoline cars, will also become redundant as EVs become more prevalent in the market. However, amidst these disappearing parts, there are emerging opportunities in the automotive industry. The rise of EVs will necessitate new areas of expertise, such as battery diagnostics, charging infrastructure installation, and software updates, creating new job opportunities for trained technicians. Furthermore, there will be a growing focus on software and electronics as they play a bigger role in car functionality. This shift emphasizes the importance of upskilling existing technicians in these areas to capitalize on new avenues within the automotive sector, aligning with the evolving landscape of electric mobility.","PeriodicalId":7357,"journal":{"name":"Advances in Mechanical Engineering","volume":"45 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141780748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The suspension system plays a critical role in automobiles, ensuring the safety and comfort of vehicle occupants. However, extended usage, varying road conditions, external forces, and heavy loads can result in damage and faults within the internal components of the suspension system. To mitigate the occurrence of suspension system failures, the development of an effective fault diagnosis system for suspension components becomes imperative. Traditional fault diagnosis techniques often heavily rely on human expertise, which comes with certain limitations. In response, researchers have embraced intelligent fault diagnosis techniques, with transfer learning-based fault diagnosis emerging as a highly effective approach. By leveraging transfer learning, it becomes possible to extract and select fault-specific features for classification purposes. Deep learning-based methods, with their capacity to extract significant features and essential information from raw data, offer notable advantages. Despite these advantages, the implementation of deep learning-based fault diagnosis in suspension systems remains relatively unexplored and limited. In this article, a deep transfer learning architecture specifically designed for fault diagnosis in suspension systems is proposed. The approach involves employing 12 pre-trained networks and tuning them to identify the optimal model for fault diagnosis. Time domain vibration signals obtained from suspension systems under seven fault conditions and one good condition are transformed into spectrogram images. These images are then pre-processed and used as input for the pre-trained networks in fault classification. The results demonstrate that among the 12 pre-trained networks, AlexNet outperforms the others in terms of classification accuracy while requiring the least amount of training time. Therefore, AlexNet network in conjunction with the spectrogram images of time domain vibration signals for applications in suspension system fault diagnosis is highly recommend.
{"title":"Deep transfer learning architecture for suspension system fault diagnosis using spectrogram image and CNN","authors":"Parameshwaran Arun Balaji, Sridharan Naveen Venkatesh, Vaithiyanathan Sugumaran, Vetri Selvi Mahamuni","doi":"10.1177/16878132241258904","DOIUrl":"https://doi.org/10.1177/16878132241258904","url":null,"abstract":"The suspension system plays a critical role in automobiles, ensuring the safety and comfort of vehicle occupants. However, extended usage, varying road conditions, external forces, and heavy loads can result in damage and faults within the internal components of the suspension system. To mitigate the occurrence of suspension system failures, the development of an effective fault diagnosis system for suspension components becomes imperative. Traditional fault diagnosis techniques often heavily rely on human expertise, which comes with certain limitations. In response, researchers have embraced intelligent fault diagnosis techniques, with transfer learning-based fault diagnosis emerging as a highly effective approach. By leveraging transfer learning, it becomes possible to extract and select fault-specific features for classification purposes. Deep learning-based methods, with their capacity to extract significant features and essential information from raw data, offer notable advantages. Despite these advantages, the implementation of deep learning-based fault diagnosis in suspension systems remains relatively unexplored and limited. In this article, a deep transfer learning architecture specifically designed for fault diagnosis in suspension systems is proposed. The approach involves employing 12 pre-trained networks and tuning them to identify the optimal model for fault diagnosis. Time domain vibration signals obtained from suspension systems under seven fault conditions and one good condition are transformed into spectrogram images. These images are then pre-processed and used as input for the pre-trained networks in fault classification. The results demonstrate that among the 12 pre-trained networks, AlexNet outperforms the others in terms of classification accuracy while requiring the least amount of training time. Therefore, AlexNet network in conjunction with the spectrogram images of time domain vibration signals for applications in suspension system fault diagnosis is highly recommend.","PeriodicalId":7357,"journal":{"name":"Advances in Mechanical Engineering","volume":"38 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141506975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-24DOI: 10.1177/16878132241262578
Lianqing Yu, Tiandu Zhou, Mingzhi Wang, Yujin Wang
With aim to reduce the energy consumption, a trajectory planning method is presented for a closed five-bow-shaped bar linkage, which can be propelled itself by morphing configuration. The objective herein is to optimize the driving joints trajectories within the global feasible region when the linkage rolls along the ground with a desired acceleration. The driving joint trajectories were represented by finite Fourier series, whose coefficients were solved by genetic algorithm to ensure a minimal energy consumption of the linkage. The impact of the number of terms of finite Fourier series on the energy consumption was also discussed through numerical examples. As a result, the energy consumption based on this strategy had been reduced by 19%, comparing with the constant potential energy strategy. A number of terms between six and eight using to denote the joint trajectories are appropriate, because that a small number of terms is incapable of expressing the joint trajectories accurately, whereas, a large number makes the joints to be subjected to vibration shock. At last, simulation on a virtual model and experiments on a prototype were carried out to verify the effectiveness of the proposed method.
{"title":"Trajectory planning of a closed five-bow-shaped bar linkage based on finite Fourier series","authors":"Lianqing Yu, Tiandu Zhou, Mingzhi Wang, Yujin Wang","doi":"10.1177/16878132241262578","DOIUrl":"https://doi.org/10.1177/16878132241262578","url":null,"abstract":"With aim to reduce the energy consumption, a trajectory planning method is presented for a closed five-bow-shaped bar linkage, which can be propelled itself by morphing configuration. The objective herein is to optimize the driving joints trajectories within the global feasible region when the linkage rolls along the ground with a desired acceleration. The driving joint trajectories were represented by finite Fourier series, whose coefficients were solved by genetic algorithm to ensure a minimal energy consumption of the linkage. The impact of the number of terms of finite Fourier series on the energy consumption was also discussed through numerical examples. As a result, the energy consumption based on this strategy had been reduced by 19%, comparing with the constant potential energy strategy. A number of terms between six and eight using to denote the joint trajectories are appropriate, because that a small number of terms is incapable of expressing the joint trajectories accurately, whereas, a large number makes the joints to be subjected to vibration shock. At last, simulation on a virtual model and experiments on a prototype were carried out to verify the effectiveness of the proposed method.","PeriodicalId":7357,"journal":{"name":"Advances in Mechanical Engineering","volume":"162 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141506973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Today motion simulators are being produced rely on electric actuators. The conventional way of dealing with high velocity, accelerations, and bulky payload is using a bigger actuator, but this leads to increased power usage and costs. To overcome these limitations, an optimized design of the Stewart platform design parameter improves simulators’ ability to support the weight of the equipment and satisfy the desired velocity and acceleration. However, it is challenging to set platform design parameters to maintain efficiency across the entire workspace. In this article, the kinematics and dynamics of the six-axis general Stewart robot are explored. A high-rated desired velocity and acceleration for the Stewart platform are defined and simulated. Then, the electric actuator force during some motion trajectory based on the defined workspace, velocity, and acceleration are calculated. Particle Swarm Optimization (PSO) is employed to optimize platform design parameters. The algorithm defines a cost function to minimize the maximum speed and maximum Force of the actuator by examining the structural kinematics arrangement of design parameters. Findings demonstrate that optimized design parameters have been successful in reducing the maximum actuator power 88.3%. Additionally, improves Stewart platform mechanical components’ life. These procedures can be employed for any Stewart platform.
{"title":"Optimization of dynamic parameter design of Stewart platform with Particle Swarm Optimization (PSO) algorithm","authors":"Masood Shahbazi, Mohammadreza Heidari, Milad Ahmadzadeh","doi":"10.1177/16878132241263940","DOIUrl":"https://doi.org/10.1177/16878132241263940","url":null,"abstract":"Today motion simulators are being produced rely on electric actuators. The conventional way of dealing with high velocity, accelerations, and bulky payload is using a bigger actuator, but this leads to increased power usage and costs. To overcome these limitations, an optimized design of the Stewart platform design parameter improves simulators’ ability to support the weight of the equipment and satisfy the desired velocity and acceleration. However, it is challenging to set platform design parameters to maintain efficiency across the entire workspace. In this article, the kinematics and dynamics of the six-axis general Stewart robot are explored. A high-rated desired velocity and acceleration for the Stewart platform are defined and simulated. Then, the electric actuator force during some motion trajectory based on the defined workspace, velocity, and acceleration are calculated. Particle Swarm Optimization (PSO) is employed to optimize platform design parameters. The algorithm defines a cost function to minimize the maximum speed and maximum Force of the actuator by examining the structural kinematics arrangement of design parameters. Findings demonstrate that optimized design parameters have been successful in reducing the maximum actuator power 88.3%. Additionally, improves Stewart platform mechanical components’ life. These procedures can be employed for any Stewart platform.","PeriodicalId":7357,"journal":{"name":"Advances in Mechanical Engineering","volume":"9 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141506974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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