【摘要】 文中对高压断路器机械故障诊断方法进行了研究,通过监测高压断路器合闸操作振动信号,提出了一种基于小波分解和支持向量机(SVM)的机械故障智能诊断方法。首先利用小波分解对振动信号进行分解,然后提取出振动信号的低频和高频重构信号的能量并将其作为特征量,最后利用SVM实现高压断路器机械故障的分类。为了验证提出的方法,搭建了高压断路器机械故障诊断软硬件平台,并对现场的高压断路器进行了实验研究。实验结果表明,该方法能有效地完成高压断路器机械故障的诊断。更多还原

【Abstract】 Research on the mechanical fault diagnosis of high voltage breakers is carried out in this paper. By monitoring the vibration signal of high voltage circuit breakers at the instant of closing operation, an intelligent diagnosis method for mechanical faults with wavelet decomposition and support vector machine is proposed. Firstly, wavelet decomposition is used to decompose the vibration signal, and then the reconstruction signal energy of low frequency and high frequency signals is extracted from the vibration signal and selected as the fault indicator. Finally, the mechanical faults of high voltage breakers is classified by using support vector machine. In order to validate the proposed method, the hardware and software of mechanical fault diagnosis system for high voltage breakers has been built, and the experiments on high voltage circuit breaker have been implemented. The experimental results show that the proposed method can effectively diagnose mechanical failure of high voltage circuit breaker.更多还原