Fault diagnosis and classification in urban rail vehicle auxiliary inverter based on wavelet packet and elman neural network

被引：0
作者：
机构：
[1] State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University Beijing
[2] Guangzhou Metro, Guangzhou
来源：
Yao, D. (shmily137@sina.com) | 2013年 / International Hellenic University - School of Science卷 / 06期
关键词：
Elman neural network; Fault diagnosis; Urban rail vehicle auxiliary inverter; Wavelet packet;
D O I：
10.25103/jestr.062.31
中图分类号：
学科分类号：
摘要：
In this paper we present a novel method in fault recognition and classification in urban rail vehicle auxiliary inverter based on wavelet packet and Elman neural network. First, the original fault voltage signals are decomposed by wavelet packet. Next, an automatic feature extraction algorithm is constructed. Finally, those wavelet packet energy eigenvectors are used as Elman neural network input parameters to realize intelligent fault diagnosis. The result shows that the Elman neural network is better than BP neural network, it is effective to distinguish the state of the urban rail vehicle auxiliary inverter. © 2013 Kavala Institute of Technology.
引用
收藏
页码：150 / 154
页数：4
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