现代电子技术2011，Vol.34Issue(5)：183-186,4.
基于小波神经网络的三相整流电路的故障诊断
Fault Diagnosis of Three-phase Rectifier Based on Wavelet Neural Network
靳芳华 1何玉珠 1张庆荣1
作者信息
- 1. 北京航空航天大学仪器科学与光电工程学院,北京100191
- 折叠
摘要
Abstract
Some problems such as low convergence rate, small searching space and oscillation are existed in the fault diagnosis of three-phase rectifier by using neural network, an improved wavelet neural network algorithm for fault diagnosis of the thyristor of three-phase rectifier is proposed in which the momentum coefficient and alter-learning coefficient are used to resolve above problems. First, according to different output waveforms caused by different faults of thyristor, using the Multisim software to simulate the faults of three-phase rectifier, then training a modified neural network with sampling data of mal-functioning waveforms, and adopting a well trained neural network to diagnose the malfunction. The simulation demonstrates that the proposed method can provide higher diagnostic precision and require less convergence time than existing methods.关键词
故障诊断/小波神经网络/晶闸管/三相整流电路分类
信息技术与安全科学引用本文复制引用
靳芳华,何玉珠,张庆荣..基于小波神经网络的三相整流电路的故障诊断[J].现代电子技术,2011,34(5):183-186,4.
