Detection and Diagnosis of Urban Rail Vehicle Auxiliary Inverter Using Wavelet Packet and RBF Neural Network

• 作者: Dechen Yao Guangwu Liu Jing Long Lingzhi Yang Xiangli Zhong Zhaoyi Su
• 来源期刊: 智能学习系统与应用(英文)
• 学科: 医学
• 关键词: Fault DIAGNOSIS Urban RAIL Vehicle AUXILIARY INVERTER WAVELET PACKET RBF Neural Network
• 年，卷（期）: 2013,（4）
• 页码范围: 211-215
• 页数: 5页
• 分类号: R73

摘要

This study concerns with fault diagnosis of urban rail vehicle auxiliary inverter using wavelet packet and RBF neural network. Four statistical features are selected: standard voltage signal, voltage fluctuation signal, impulsive transient signal and frequency variation signal. In this article, the original signals are decomposed into different frequency subbands by wavelet packet. Next, an automatic feature extraction algorithm is constructed. Finally, those wavelet packet energy eigenvectors are taken as fault samples to train RBF neural network. The result shows that the RBF neural network is effective in the detection and diagnosis of various urban rail vehicle auxiliary inverter faults.