On-line fault diagnosis model for locomotive traction inverter based on wavelet transform and support vector machine

被引：29
|
作者：
Mei Fei [1 ]
Liu Ning [1 ]
Miao Huiyu [2 ]
Pan Yi [2 ]
Sha Haoyuan [2 ]
Zheng Jianyong [2 ]
机构：
[1] Hohai Univ, Coll Energy & Elect Engn, Nanjing 211100, Jiangsu, Peoples R China
[2] Southeast Univ, Sch Elect Engn, Nanjing 210096, Jiangsu, Peoples R China
来源：
MICROELECTRONICS RELIABILITY | 2018年 / 88-90卷
基金：
中国博士后科学基金;
关键词：
Locomotive traction inverter; Fault diagnosis; Wavelet transform; Support vector machine;
D O I：
10.1016/j.microrel.2018.06.069
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A traction inverter is the power source for rail transit vehicles. An insulated-gate bipolar transistor (IGBT) is the primary component of a traction inverter. IGBT faults can cause serious problems in locomotive power supply systems. The disadvantage of traditional fault detection methods for IGBT modules is a lack of real-time processing and high efficiency. An on-line fault diagnosis method based on a wavelet transform and multi-classification support vector machine (multi-SVM) is proposed for IGBT faults. Wavelet decomposition is used to process fault current signals, and energy vectors are constructed. Multi-SVM is used to establish a fault recognition model. The validity of this method is verified by simulations with MATLAB/Simulink.
引用
收藏
页码：1274 / 1280
页数：7
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