一种基于振动信号的高压断路器故障诊断新方法

A New Method of Fault Diagnosis for High Voltage Circuit Breakers Based on Vibration Signals

提出一种以小波包特征节点最大系数为特征向量、利用支持向量机状态分类的断路器故障诊断新方法。首先利用小波包分解振动数据,提取状态变化敏感节点作为特征节点形成分解树,利用敏感节点重构完好状态振动信号,并以此作为当前大多断路器诊断系统中使用的指纹信号;同时提取特征节点最大系数形成特征向量,作为支持向量机的输入向量,使用“一对其余”策略进行特征分类。经高压断路器无负载振动信号测试,该方法检测高压断路器故障简单、准确,在实际分析中取得良好诊断效果。

A new method of fault diagnosis based on wavelet packet and support vector machine is presented. Wavelet packet decompresses vibration signals, and wavelet packet nodes which are sensitive to the change of state, as eigen-nodes, form a decomposition tree; the signal restructured at all eigen-nodes can be used as the fingerprint in many breaker diagnostic systems. Support vector machine with the ＂most important＂ factors at eigen-nodes as input vector classifies the states at ＂one to others＂ strategy. The experimentation without loads indicates the method can easily and accurately diagnose breaker faults.