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Multiple-Model-Based Diagnosis of Multiple Faults With High-Speed Train Applications Using Second-Level Adaptation

Authors :
Fuyang Chen
Bin Jiang
Kunpeng Zhang
Source :
IEEE Transactions on Industrial Electronics. 68:6257-6266
Publication Year :
2021
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2021.

Abstract

Due to the time-varying characteristics and the interacted nature of multiple faults in the high-speed train (HST), the fault modeling, isolation, and severity estimation cannot be described accurately using a single model, which may result in poor performance of the conventional fault diagnosis methods. This article introduces the idea of multiple models and second-level adaptation techniques to diagnose multiple faults of the HST traction motor. First, a reduced model description for the multiple faults is given. Then, a multiple fault isolation framework is developed to simplify the time-varying fault parameters space segmentation. Based on the decoupled fault set, a fault estimation scheme with second-level adaptation is used to provide a reliable alarm priority for different fault scenarios. A case study is performed to verify the effectiveness of the proposed approach.

Details

ISSN :
15579948 and 02780046
Volume :
68
Database :
OpenAIRE
Journal :
IEEE Transactions on Industrial Electronics
Accession number :
edsair.doi...........fa88258545e6ffac216faa9424a7a6aa
Full Text :
https://doi.org/10.1109/tie.2020.2994867