Fault Diagnosis of Analog Circuit Based on Multi-Test Points and Multi-Feature Information

摘要：

　　In the process of use BP neural network to fault diagnosis of analog circuits,the network input which represents fault signature was very important.A given new method which base on multi-points and multi-feature information is taken to construct the original sample set.With this method to construct the original fault signature set,then as the input of BP neural network and train the network.Simulation results show that,the network train with sample set which constructed by this method use in fault diagnosis of analog circuits is better accuracy than traditional methods.Proved the feasibility of this method in fault diagnosis of analog circuits,and offer a new method for fault diagnosis of analog circuits.

关键词： BP neural network analog circuits fault diagnosis fault feature

作者: Pan Qiang Yang Chao

作者单位: Electronic Engineering College,Naval University of Engineering,Wuhan 430033,China

会议类型: 国际会议

会议名称: 2012 2nd International conference on Machinery Electronics and Control Engineering (2012年第二届国际机械电子与控制工程会议(ICMECE 2012))

会议地点: 济南

会议语种:英文

页码: 277-280

在线出版日期: 2012-12-29（万方平台首次上网日期，不代表论文的发表时间）