A Variable Load Fault Detection and Diagnosis Method for Traction Systems of High-speed Trains

The traction systems of high-speed trains operate under variable load conditions, which induce significant variations in system data characteristics. Traditional methods usually use a unified global model to describe the traction system, but this approach easily ignores the local features of the dat...

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Bibliographic Details
Published in:International journal of control, automation, and systems Vol. 23; no. 9; pp. 2599 - 2610
Main Authors: Li, Xuedong, Wang, Hongzhi, Wan, Zhiwei, Cheng, Chao
Format: Journal Article
Language:English
Published: Bucheon / Seoul Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers 01.09.2025
Springer Nature B.V
제어·로봇·시스템학회
Subjects:
Control
Engineering
False alarms
Fault detection
Fault diagnosis
High speed rail
Load
Mechatronics
Methods
Neural networks
Nonlinear systems
Regular Papers
Robotics
System effectiveness
제어계측공학
traction systems of high-speed trains
Conditional variational autoencoder (CVAE)
fault detection and diagnosis (FDD)
variable loads
ISSN:2005-4092, 1598-6446, 2005-4092
Online Access:Get full text
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Summary:The traction systems of high-speed trains operate under variable load conditions, which induce significant variations in system data characteristics. Traditional methods usually use a unified global model to describe the traction system, but this approach easily ignores the local features of the data, resulting in an increase in false alarm rate. Therefore, this paper proposes a new data-driven FDD method based on a conditional variational autoencoder (CVAE) to address this challenge. The key advantages of the proposed method include: 1) The proposed method significantly improves the sensitivity and reliability of fault detection under variable loads. 2) The proposed FDD framework does not require precise physical models or system-specific parameters, making it highly adaptable. 3) The proposed method can be readily extended to other nonlinear industrial systems. The effectiveness of the proposed method is validated on a traction system of a high-speed train simulation platform.
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http://link.springer.com/article/10.1007/s12555-024-1205-5
ISSN:2005-4092
1598-6446
2005-4092
DOI:10.1007/s12555-024-1205-5