计算机与现代化 ›› 2012, Vol. 1 ›› Issue (9): 181-183,.doi: 0.3969/j.issn.1006-2475.2012.09.046

• 算法分析与设计 • 上一篇    下一篇

基于小波变换多分辨率特征提取的模拟电路故障诊断方法研究

李论,李志华   

  1. 河海大学能源与电气学院,江苏南京211100
  • 收稿日期:2012-05-08 修回日期:1900-01-01 出版日期:2012-09-21 发布日期:2012-09-21

A Method for Fault Diagnosis of Analog Circuits Based on Wavelet Multi-resolution Feature Extraction

LI Lun, LI Zhi-hua   

  1. College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
  • Received:2012-05-08 Revised:1900-01-01 Online:2012-09-21 Published:2012-09-21

摘要: 提出一种基于小波变换多分辨率特征提取的模拟电路故障诊断的方法。该方法先对采样后的故障信号进行小波分解,提取各频段系数作为特征向量输入到神经网络进行训练。通过带通滤波器电路诊断的实例,阐述该方法的具体实现,验证该方法可以有效地简化神经网络结构和减少它的训练时间,快速高效地进行模拟电路故障的诊断和定位。

关键词: 小波分析, 神经网络, 模拟电路, 故障诊断

Abstract: This paper researches the method based on the wavelet multi-resolution feature extraction for analog circuit fault diagnosis. The features of sampling signal are extracted from wavelet decomposition as a vector to BP neural network for training. According to bandpass filter circuit of diagnosis example, this paper discusses the specific implementation of this method. It can effectively simplify neural network structure and reduce its training time, quickly and efficiently carry out analog circuit fault diagnosis and positioning.

Key words: wavelet analysis, neural network, analogue circuits, fault diagnosis