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Vehicle System Dynamics
International Journal of Vehicle Mechanics and Mobility
Volume 52, 2014 - Issue 6
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Original Articles

On fault isolation for rail vehicle suspension systems

Xiukun WeiState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing100044, China;School of Traffic and Transportation, Beijing Jiaotong University, Beijing100044, ChinaCorrespondence[email protected]
,
Limin JiaState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing100044, ChinaCorrespondence[email protected]
,
Kun GuoSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing100044, China
&
Sheng WuSchool of Automation, Beijing University of Science and Technology, Beijing100083, China
Pages 847-873 | Received 08 Aug 2013, Accepted 11 Mar 2014, Published online: 10 Apr 2014

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N. Bosso, M. Magelli, R. Trinchero & N. Zampieri. (2024) Application of machine learning techniques to build digital twins for long train dynamics simulations. Vehicle System Dynamics 62:1, pages 21-40.
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G. Vlachospyros, S. D. Fassois & J. S. Sakellariou. (2023) On-board vibration-based robust and unsupervised degradation detection in railway suspensions under various travelling speeds via a Multiple Model framework. Vehicle System Dynamics 0:0, pages 1-25.
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Chunsheng Li, Shihui Luo, Colin Cole & Maksym Spiryagin. (2018) Bolster spring fault detection strategy for heavy haul wagons. Vehicle System Dynamics 56:10, pages 1604-1621.
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Chunsheng Li, Shihui Luo, Colin Cole, Maksym Spiryagin & Yanquan Sun. (2017) A signal-based fault detection and classification method for heavy haul wagons. Vehicle System Dynamics 55:12, pages 1807-1822.
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Seyed Milad Mousavi Bideleh. (2017) Robustness analysis of bogie suspension components Pareto optimised values. Vehicle System Dynamics 55:8, pages 1189-1205.
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Chunsheng Li, Shihui Luo, Colin Cole & Maksym Spiryagin. (2017) An overview: modern techniques for railway vehicle on-board health monitoring systems. Vehicle System Dynamics 55:7, pages 1045-1070.
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Mehdi Taheri & Mehdi Ahmadian. (2016) Machine learning from computer simulations with applications in rail vehicle dynamics. Vehicle System Dynamics 54:5, pages 653-666.
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Funing Yang, Jikai Liu, Chunrong Hua, Weiqun Liu & Dawei Dong. Early fault diagnosis strategy for high-speed train suspension systems based on model-agnostic meta-learning. Vehicle System Dynamics 0:0, pages 1-23.
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Articles from other publishers (26)

H. Leela Karthikeyan, Naveen Venkatesh Sridharan, P. Arun Balaji & Sugumaran Vaithiyanathan. (2024) Diagnosing Faults in Suspension System Using Machine Learning and Feature Fusion Strategy. Arabian Journal for Science and Engineering.
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Pedro Moreira Ordiales Millan, João Emanuel Carvalho Pagaimo, João Neves Costa, Nuno Manuel Mendes Maia & Jorge Alberto Cadete Ambrósio. (2023) On the use of transmissibility for the detection of damaged springs in the primary suspension of a locomotive. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 238:2, pages 237-248.
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Mohan Zhang, Bo Yin, Zhenxu Sun, Ye Bai & Guowei Yang. (2024) A feasibility study on applying meta-heuristic optimization and Gaussian process regression for predicting the performance of pantograph-catenary system应用元启发式优化和高斯过程回归预测受电弓-接触网系统性能的可行性研究. Acta Mechanica Sinica 40:1.
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Dingcheng Zhang, Min Xie, Jingyuan Yang & Tao Wen. (2023) Multi-Sensor Graph Transfer Network for Health Assessment of High-Speed Rail Suspension Systems. IEEE Transactions on Intelligent Transportation Systems 24:9, pages 9425-9434.
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Hector A. Fernandez-Bobadilla & Ullrich Martin. (2023) Modern Tendencies in Vehicle-Based Condition Monitoring of the Railway Track. IEEE Transactions on Instrumentation and Measurement 72, pages 1-44.
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Tuo Xu, Ping Xu, Hui Zhao, Chengxing Yang & Yong Peng. (2023) Vehicle running attitude prediction model based on Artificial Neural Network-Parallel Connected (ANN-PL) in the single-vehicle collision. Advances in Engineering Software 175, pages 103356.
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Na Qin, Bi Wu, Deqing Huang & Yiming Zhang. (2022) Stepwise Adaptive Convolutional Network for Fault Diagnosis of High-Speed Train Bogie Under Variant Running Speeds. IEEE Transactions on Industrial Informatics 18:12, pages 8389-8398.
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Funing Yang, Lumei Lv, Chunrong Hua, Libo Xiong & Dawei Dong. (2022) Fault diagnosis of suspension system of high-speed train based on model-agnostic meta-learning. Fault diagnosis of suspension system of high-speed train based on model-agnostic meta-learning.
Rui Ding, Linyu Du, Yiming Du, Jun Fu, Yuqi Zhu, Yilin Zhang & Lina Peng. (2022) Study on the Evolution and Resilience of Rail Transit Time Networks—Evidence from China. Applied Sciences 12:19, pages 9950.
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Xinming Jia, Na Qin, Deqing Huang, Yiming Zhang & Jiahao Du. (2022) A clustered blueprint separable convolutional neural network with high precision for high-speed train bogie fault diagnosis. Neurocomputing 500, pages 422-433.
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Mădălina Dumitriu. (2022) Condition Monitoring of the Dampers in the Railway Vehicle Suspension Based on the Vibrations Response Analysis of the Bogie. Sensors 22:9, pages 3290.
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Yiming Zhang, Na Qin, Deqing Huang, Bi Wu & Ziyi Liu. (2022) High-Accuracy and Adaptive Fault Diagnosis of High-Speed Train Bogie Using Dense-Squeeze Network. IEEE Transactions on Vehicular Technology 71:3, pages 2501-2510.
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Yunguang Ye, Ping Huang & Yongxiang Zhang. (2021) Deep learning-based fault diagnostic network of high-speed train secondary suspension systems for immunity to track irregularities and wheel wear. Railway Engineering Science 30:1, pages 96-116.
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Hae Young Noh & Jonathon Fagert. 2022. Sensor Technologies for Civil Infrastructures. Sensor Technologies for Civil Infrastructures 639 677 .
Yu-Ru Li, Tao Zhu, Shou-Ne Xiao, Bing Yang, Guang-Wu Yang, Xiao-Lin Yuan & Zhao Tang. (2020) Application of the collision mathematical model based on a BP neural network in railway vehicles. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 235:6, pages 713-725.
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Yongbo Li, Fulong Liu, Shun Wang & Jiancheng Yin. (2021) Multiscale Symbolic Lempel–Ziv: An Effective Feature Extraction Approach for Fault Diagnosis of Railway Vehicle Systems. IEEE Transactions on Industrial Informatics 17:1, pages 199-208.
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Na Qin, Kaiwei Liang, Deqing Huang, Lei Ma & Andrew H. Kemp. (2020) Multiple Convolutional Recurrent Neural Networks for Fault Identification and Performance Degradation Evaluation of High-Speed Train Bogie. IEEE Transactions on Neural Networks and Learning Systems 31:12, pages 5363-5376.
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Ning Hong, Lishuai Li, Weiran Yao, Yang Zhao, Cai Yi, Jianhui Lin & Kwok Leung Tsui. (2020) High-Speed Rail Suspension System Health Monitoring Using Multi-Location Vibration Data. IEEE Transactions on Intelligent Transportation Systems 21:7, pages 2943-2955.
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Yu-Ru Li, Tao Zhu, Zhao Tang, Shou-Ne Xiao, Jun-Ke Xie, Zhong-Bin Liu & Shi-De Xiao. (2020) Inversion prediction of back propagation neural network in collision analysis of anti-climbing device. Advances in Mechanical Engineering 12:5, pages 168781402092205.
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T.-C.I. Aravanis, J.S. Sakellariou & S.D. Fassois. (2020) A stochastic Functional Model based method for random vibration based robust fault detection under variable non–measurable operating conditions with application to railway vehicle suspensions. Journal of Sound and Vibration 466, pages 115006.
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Fulong Liu, Jiongqi Wang, Miaoshuo Li, Fengshou Gu & Andrew D. Ball. 2020. Proceedings of the 13th International Conference on Damage Assessment of Structures. Proceedings of the 13th International Conference on Damage Assessment of Structures 166 181 .
Altan Onat & Bekir Tuna Kayaalp. (2019) A Novel Methodology for Dynamic Weigh in Motion System for Railway Vehicles With Traction. IEEE Transactions on Vehicular Technology 68:11, pages 10545-10558.
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Yanqin Teng & Xiukun Wei. (2019) Security inspection of suspension system in urban rail track based on Track-side Signal Detection. Security inspection of suspension system in urban rail track based on Track-side Signal Detection.
Zehui Mao, Yanhao Zhan, Gang Tao, Bin Jiang & Xing-Gang Yan. (2017) Sensor Fault Detection for Rail Vehicle Suspension Systems With Disturbances and Stochastic Noises. IEEE Transactions on Vehicular Technology 66:6, pages 4691-4705.
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Tengteng Wang, Xiukun Wei, Limin Jia & Guorui Zhai. (2017) Weak fault detection of rail vehicle suspension system based on MPCA. Weak fault detection of rail vehicle suspension system based on MPCA.
Rafał Melnik & Seweryn Koziak. (2017) Rail vehicle suspension condition monitoring – approach and implementation. Journal of Vibroengineering 19:1, pages 487-501.
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