电工技术学报2017，Vol.32Issue(5)：49-54,6.
基于SOM的真空断路器机械故障诊断
Mechanical Fault Diagnosis of Vacuum Circuit Breaker Based on SOM
摘要
Abstract
The basic concepts and highlights of self-organization map (SOM) neural network which is suitable for small samples are given.The relationship between mechanical characteristics of vacuum circuit breaker and the corresponding mechanical failure was analyzed.On this basis, a method of mechanical fault diagnosis of vacuum circuit breaker that mechanical characteristics parameters were taken as training and identification samples of SOM neural network is proposed.The whole process of applying this method to conduct the mechanical fault classification of circuit breakers is emphasized: the fault differentiation is carried out by extracting the mechanical characteristics of circuit breaker under the normal and fault states as inputs of SOM network.The experimental results show that the fault diagnosis scheme achieves high accuracy of mechanical fault classification for vacuum circuit breakers.关键词
真空断路器/自组织映射网络/机械特性/故障诊断Key words
Vacuum circuit breaker/self-organization map/mechanical characteristics/fault diagnosis分类
信息技术与安全科学引用本文复制引用
刘艳,陈丽安..基于SOM的真空断路器机械故障诊断[J].电工技术学报,2017,32(5):49-54,6.基金项目
福建省科技厅高校产学合作科技重大项目资助(2014H6028). （2014H6028）
