Research and Application of Fault Prediction Method for High-speed EMU Based on PHM Technology

다국어 초록 (Multilingual Abstract)

In recent years, with the rapid development of large and medium-sized urban rail transit in China, the total operating mileage of high-speed railway and the total number of EMUs(Electric Multiple Units) are rising. The system complexity of high-speed EMU is constantly increasing, which puts forward higher requirements for the safety of equipment and the efficiency of maintenance.At present, the maintenance mode of high-speed EMU in China still adopts the post maintenance method based on planned maintenance and fault maintenance, which leads to insufficient or excessive maintenance, reduces the efficiency of equipment fault handling, and increases the maintenance cost. Based on the intelligent operation and maintenance technology of PHM(prognostics and health management). This thesis builds an integrated PHM platform of "vehicle system-communication system-ground system" by integrating multi-source heterogeneous data of different scenarios of high-speed EMU, and combines the equipment fault mechanism with artificial intelligence algorithms to build a fault prediction model for traction motors of high-speed EMU.Reliable fault prediction and accurate maintenance shall be carried out in advance to ensure safe and efficient operation of high-speed EMU.

참고문헌 (Reference)

1 T. Yang, "Vehicle failure rate prediction based on BP neural network" 26 (26): 276-271, 2009

2 B. Liu, "Thoughts on the research of fault prediction and health management (PHM) system architecture of EMU" 1-9, 2022

3 Y. Li, "Research on the Application of PHM Technology in the Operation and Maintenance of Beijing Zhangjiakou High speed Railway" 44 (44): 103-111, 2022

4 J. Y. Liang, "Research on intelligent diagnosis and fault prediction technology of high-speed trains" 43 (43): 63-70, 2019

5 Q. M. Niu, "Research on intelligent analysis model of health status of high-speed railway equipment based on PHM technology" Beijing Jiaotong University 2019

6 W. T. Hu, "Research on fault prediction and health management of traction motor of multiple units" Lanzhou Jiaotong University 2021

7 X. X. Xie, "Research on fault diagnosis of uninsulated track circuit based on deep learning" 42 (42): 79-85, 2020

8 N. Zhe, "Research on fault diagnosis and residual life prediction methods of rolling bearings based on big data technology" Beijing University of chemical technology 2018

9 C. X. Li, "Research on PHM fault model and management of EMU" China Academy of Railway Sciences 2020

10 Y. G. Chi, "Research and application of fault prediction and health management technology for multiple units" 118-124, 2018

11 D. G. Song, "Research and application of big data PHM system for high-speed EMU" 27 (27): 44-48, 2018

12 X. Z. Li, "Fault diagnosis method of high-speed railway signal equipment based on deep learning integration" 42 (42): 97-105, 2020

13 K. Zhao, "Design and Implementation of PHM Big Data Architecture for Distributed High speed EMUs" 39 (39): 90-94, 2018

14 Z. Y. Wu, "Application of big data technology in EMU fault warning" 91-96, 2021

15 Z. Y. Wu, "Application of big data technology in EMU fault warning" 91-96, 2021

16 C. Z. Chi, "Analysis on development trend of aviation equipment PHM and maintenance support technology" 167-171, 2019