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Vehicle System Dynamics
International Journal of Vehicle Mechanics and Mobility
Volume 47, 2009 - Issue 9
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Original Articles

Condition monitoring of rail vehicle suspensions based on changes in system dynamic interactions

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Pages 1167-1181 | Received 17 Jul 2008, Accepted 13 Oct 2008, Published online: 13 Aug 2009

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Read on this site (16)

Yuejian Chen, Gang Niu, Yifan Li & Yongbo Li. (2023) A modified bidirectional long short-term memory neural network for rail vehicle suspension fault detection. Vehicle System Dynamics 61:12, pages 3136-3160.
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Ingo Kaiser, Salvatore Strano, Mario Terzo & Ciro Tordela. (2023) Estimation of the railway equivalent conicity under different contact adhesion levels and with no wheelset sensorization. Vehicle System Dynamics 61:1, pages 19-37.
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Jianfeng Sun, Enrico Meli, Wubin Cai, Hongxin Gao, Maoru Chi, Andrea Rindi & Shulin Liang. (2021) A signal analysis based hunting instability detection methodology for high-speed railway vehicles. Vehicle System Dynamics 59:10, pages 1461-1483.
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David Lebel, Christian Soize, Christine Funfschilling & Guillaume Perrin. (2020) High-speed train suspension health monitoring using computational dynamics and acceleration measurements. Vehicle System Dynamics 58:6, pages 911-932.
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Fulong Liu, Hao Zhang, Xiaocong He, Yunshi Zhao, Fengshou Gu & Andrew D. Ball. (2020) Correlation signal subset-based stochastic subspace identification for an online identification of railway vehicle suspension systems. Vehicle System Dynamics 58:4, pages 569-589.
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Christine Funfschilling & Guillaume Perrin. (2019) Uncertainty quantification in vehicle dynamics. Vehicle System Dynamics 57:7, pages 1062-1086.
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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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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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Tryfon-Chrysovalantis I. Aravanis, John S. Sakellariou & Spilios D. Fassois. (2016) Spectral analysis of railway vehicle vertical vibration under normal operating conditions. International Journal of Rail Transportation 4:4, pages 193-207.
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X.Y. Liu, S. Alfi & S. Bruni. (2016) An efficient recursive least square-based condition monitoring approach for a rail vehicle suspension system. Vehicle System Dynamics 54:6, pages 814-830.
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Mathias Jesussek & Katrin Ellermann. (2014) Fault detection and isolation for a full-scale railway vehicle suspension with multiple Kalman filters. Vehicle System Dynamics 52:12, pages 1695-1715.
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Xiukun Wei, Limin Jia, Kun Guo & Sheng Wu. (2014) On fault isolation for rail vehicle suspension systems. Vehicle System Dynamics 52:6, pages 847-873.
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Mathias Jesussek & Katrin Ellermann. (2013) Fault detection and isolation for a nonlinear railway vehicle suspension with a Hybrid Extended Kalman filter. Vehicle System Dynamics 51:10, pages 1489-1501.
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Xiukun Wei, Limin Jia & Hai Liu. (2013) A comparative study on fault detection methods of rail vehicle suspension systems based on acceleration measurements. Vehicle System Dynamics 51:5, pages 700-720.
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Livio Gasparetto, Stefano Alfi & Stefano Bruni. (2013) Data-driven condition-based monitoring of high-speed railway bogies. International Journal of Rail Transportation 1:1-2, pages 42-56.
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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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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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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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Yanxiang Chen, Zuxing Zhao, Euiyoul Kim, Haiyang Liu, Juan Xu, Hai Min & Yong Cui. (2021) Wheel fault diagnosis model based on multichannel attention and supervised contrastive learning. Advances in Mechanical Engineering 13:12, pages 168781402110670.
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Mariusz Kostrzewski & Rafał Melnik. (2021) Condition Monitoring of Rail Transport Systems: A Bibliometric Performance Analysis and Systematic Literature Review. Sensors 21:14, pages 4710.
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Ingo Kaiser, Salvatore Strano, Mario Terzo & Ciro Tordela. (2021) Anti-yaw damping monitoring of railway secondary suspension through a nonlinear constrained approach integrated with a randomly variable wheel-rail interaction. Mechanical Systems and Signal Processing 146, pages 107040.
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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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Yunguang Ye, Yongxiang Zhang, Qingbo Wang, Zhiwei Wang, Zhenjie Teng & Hougui Zhang. (2020) Fault diagnosis of high-speed train suspension systems using multiscale permutation entropy and linear local tangent space alignment. Mechanical Systems and Signal Processing 138, pages 106565.
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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 .
Min Dong, Gang Tao, Liyan Wen & Bin Jiang. (2019) Adaptive Sensor Fault Detection for Rail Vehicle Suspension Systems. IEEE Transactions on Vehicular Technology 68:8, pages 7552-7565.
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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.
Salvatore Strano & Mario Terzo. (2019) Review on model-based methods for on-board condition monitoring in railway vehicle dynamics. Advances in Mechanical Engineering 11:2, pages 168781401982679.
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M Dumitriu & M A Gheţi. (2018) Numerical study on the influence of primary suspension damping upon the dynamic behaviour of railway vehicles. IOP Conference Series: Materials Science and Engineering 444, pages 042001.
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M Dumitriu & M A Gheţi. (2018) Influence of the interference of bounce and pitch vibrations upon the dynamic behaviour in the bogie of a railway vehicle. IOP Conference Series: Materials Science and Engineering 400, pages 042020.
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Huiming Yao, Cristian Ulianov & Feng Liu. (2018) Joint Self-learning and Fuzzy Clustering Algorithm for Early Warning Detection of Railway Running Gear Defects. Joint Self-learning and Fuzzy Clustering Algorithm for Early Warning Detection of Railway Running Gear Defects.
Mariusz Kostrzewski. (2018) Analysis of selected acceleration signals measurements obtained during supervised service conditions – study of hitherto approach. Journal of Vibroengineering 20:4, pages 1850-1866.
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Caglar Uyulan, Metin Gokasan & Seta Bogosyan. (2017) Comparison of the re-adhesion control strategies in high-speed train. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 232:1, pages 92-105.
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Mariusz Kostrzewski. (2017) Analysis of selected vibroacoustic signals recorded on EMU vehicle running on chosen routes under supervised operating conditions. Vibroengineering PROCEDIA 13, pages 153-158.
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Fulong Liu, Fengshou Gu, Andrew D. Ball, Yunshi Zhao & Bo Peng. (2017) The validation of an ACS-SSI based online condition monitoring for railway vehicle suspension systems using a SIMPACK model. The validation of an ACS-SSI based online condition monitoring for railway vehicle suspension systems using a SIMPACK model.
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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Dhiraj Sinha & Farhan Feroz. (2016) Obstacle Detection on Railway Tracks Using Vibration Sensors and Signal Filtering Using Bayesian Analysis. IEEE Sensors Journal 16:3, pages 642-649.
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Bin Xu, Jianwu Zhang & Xiqiang Guan. (2014) Estimation of the parameters of a railway vehicle suspension using model-based filters with uncertainties. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 229:7, pages 785-797.
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Kym Fraser, Hans-Henrik Hvolby & Tzu-Liang (Bill) Tseng. (2015) Maintenance management models: a study of the published literature to identify empirical evidence. International Journal of Quality & Reliability Management 32:6, pages 635-664.
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John S. Sakellariou, Konstantinos A. Petsounis & Spilios D. Fassois. (2015) Vibration based fault diagnosis for railway vehicle suspensions via a functional model based method: A feasibility study. Journal of Mechanical Science and Technology 29:2, pages 471-484.
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Mathias Jesussek & Katrin Ellermann. (2015) Fault Detection and Isolation for a Railway Vehicle by Evaluating Estimation Residuals. Procedia IUTAM 13, pages 14-23.
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Ning Ren & Min Yue Fu. (2014) Condition monitoring of train suspension systems using a cross-correlation technique. Condition monitoring of train suspension systems using a cross-correlation technique.
Xiukun Wei, Limin Jia, Kun Guo & Sheng Wu. (2014) Fault Isolation for Urban Railway Vehicle Suspension Systems. IFAC Proceedings Volumes 47:3, pages 12122-12127.
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Yanping Du, Yuan Zhang, Xiaogang Zhao & Xiaohui Wang. (2014) Risk Evaluation of Bogie System Based on Extension Theory and Entropy Weight Method. Computational Intelligence and Neuroscience 2014, pages 1-6.
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Peter Hubbard, Chris Ward, Roger Dixon & Roger Goodall. (2013) Real time detection of low adhesion in the wheel/rail contact. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 227:6, pages 623-634.
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Bartosz Firlik, Bartosz Czechyra & Andrzej Chudzikiewicz. (2012) Condition Monitoring System for Light Rail Vehicle and Track. Key Engineering Materials 518, pages 66-75.
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Rafał Melnik & Mariusz Kostrzewski. (2012) Rail Vehicle's Suspension Monitoring System - Analysis of Results Obtained in Tests of the Prototype. Key Engineering Materials 518, pages 281-288.
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