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LI Yi-fan, LIU Jian-xin, LIN Jian-hui, LI Zhong-ji. Fault diagnosis method of railway vehicle with wheel flat based on self-adaptive multi-scale morphology analysis[J]. Journal of Traffic and Transportation Engineering, 2015, 15(1): 58-65. doi: 10.19818/j.cnki.1671-1637.2015.01.008
Citation: LI Yi-fan, LIU Jian-xin, LIN Jian-hui, LI Zhong-ji. Fault diagnosis method of railway vehicle with wheel flat based on self-adaptive multi-scale morphology analysis[J]. Journal of Traffic and Transportation Engineering, 2015, 15(1): 58-65. doi: 10.19818/j.cnki.1671-1637.2015.01.008
shu

Fault diagnosis method of railway vehicle with wheel flat based on self-adaptive multi-scale morphology analysis

doi: 10.19818/j.cnki.1671-1637.2015.01.008
  • 1.

    E'mei Campus Department of Mechanical Engineering, Southwest Jiaotong University, E'mei 614202, Sichuan, China

  • 2.

    State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, Sichuan, China

  • 3.

    Institute of Science and Technology, China Railway Eryuan Engineering GroupCo., Ltd., Chengdu 610031, Sichuan, China

More Information
  • Author Bio:

    LI Yifan(1985-), male, lecturer, PhD, + 86-833-5198322, Liyifan@swjtu.edu.cn

  • Received Date: 2014-07-08
  • Publish Date: 2015-02-25
    Abstract
  • A vehicle system dynamics model with 56 degrees of freedom and a wheel flat model were set up to calculate railway vehicle dynamic responses.The vibration information of vehicle was often influenced by various interferences, such as track irregularity and vehicle speed alteration.In order to effectively extract the wheel-track impact features from strong background noises, a self-adaptive multi-scale morphology filtering analysis algorithm was proposed to study the axle box vibration characteristics caused by wheel flat.The influences of track irregularity and vehicle running speed on the fault diagnosis result of axle box were discussed.Simulation result shows that the fault frequencies of 10, 15, 20 Hz are obtained by using morphology filter based on 7-scale and 9-scale structural elements at the speeds of 100, 150, 200km·h-1 with the American fifth grade and third grade track irregularities.Test result demonstrates that the fault frequency of 2 Hz is obtained by using morphology filter based on 7-scale structural element atthe speed of 40km·h-1, which is corresponding to the theoretic frequency of wheel flat, so diagnosis result is reliable.

     

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