基于小波奇异性和神经网络的高压断路器机械故障诊断  

Mechanical Fault Diagnosis of High Voltage Breakers Based on the Wavelet Singularity and Neural Network

作　　者：王芳[1] 毛晓桦[1] 

机构地区：[1]南京工程学院电力工程系,江苏南京210013

出　　处：《南京工程学院学报（自然科学版）》2005年第1期23-27,共5页Journal of Nanjing Institute of Technology(Natural Science Edition)

摘　　要：将小波奇异性检测理论与模糊神经网络相结合应用到高压断路器机械故障诊断中,这是一种新的方法.实验结果表明,该方法较之小波奇异性检测有更好的效果,提高了诊断的准确性和精度.This paper introduces a new method that combines the wavelet singularity detection with fuzzy NN to process the mechanism vibration signal of the HV breaker. The method, proved more effective and accurate than the wavelet singularity detection, applies both the wavelet singularity exponent of fuzzification and the back propagation of NN to the mechanism fault diagnosis of the HV breaker.

关 键 词：高压断路器 小波奇异性 模糊神经网络 故障诊断 

分 类 号：TM561[电气工程—电器] TP183[自动化与计算机技术—控制理论与控制工程]