Sigma-Mixed Unscented Kalman Filter-Based Fault Detection for Traction Systems in High-Speed Trains

被引：0

作者：

CHENG Chao ^{[1
]}

WANG Weijun ^{[2
]}

MENG Xiangxi ^{[3
]}

SHAO Haidong ^{[4
]}

CHEN Hongtian ^{[5
]}

机构：

[1] Department of Computer Science and Technology, Changchun University of Technology

[2] Department of Mathematics and Statistics, Changchun University of Technology

[3] Institute of System Research, China Industrial Control Systems Cyber Emergency Response Team

[4] Department of Mechanical and Vehicle Engineering, Hunan University

[5] Department of Chemical and Materials Engineering, University of Alberta

来源：

ChineseJournalofElectronics | 2023年 / 32卷 / 05期

基金：

中国国家自然科学基金;

关键词：

D O I：

暂无

中图分类号：

TP277 [监视、报警、故障诊断系统]; TN713 [滤波技术、滤波器]; U279 [车辆运用、保养与检修];

学科分类号：

080204 ; 0804 ; 080401 ; 080402 ; 080902 ; 082304 ;

摘要：

Fault detection(FD) for traction systems is one of the active topics in the railway and academia because it is the initial step for the running reliability and safety of high-speed trains. Heterogeneity of data and complexity of systems have brought new challenges to the traditional FD methods. For addressing these challenges, this paper designs an FD algorithm based on the improved unscented Kalman filter(UKF) with consideration of performance degradation. It is derived by incorporating a degradation process into the state-space model.The network topology of traction systems is taken into consideration for improving the performance of state estimation. We first obtain the mixture distribution by the mixture of sigma points in UKF. Then, the Lévy process with jump points is introduced to construct the degradation model. Finally, the moving average interstate standard deviation(MAISD) is designed for detecting faults.Verifying the proposed methods via a traction systems in a certain type of trains obtains satisfactory results.

引用

页码：982 / 991

页数：10

共 22 条

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