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高压电器  2015 

基于最小二乘支持向量机的高压断路器故障诊断

DOI: 10.13296/j.1001-1609.hva.2015.12.014, PP. 79-83

Keywords: 高压断路器,分合闸线圈电流,故障诊断,最小二乘支持向量机(LS-SVM),遗传算法

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Abstract:

为了快速、准确地对高压断路器发生的故障进行分析和诊断,确定故障的性质、类别和部位,提出了一种高压断路器故障诊断的新方法。首先对高压断路器分合闸线圈电流进行分析,提取电流和时间特征量形成特征向量,然后用遗传算法对最小二乘支持向量机(leastsquaresupportvectormachine,LS-SVM)参数进行优化,最后,将特征向量输入到优化后的最小二乘支持向量机中进行故障识别、分类。试验表明,该方法可以准确地识别断路器的多种故障类型,为断路器故障定位和状态检修提供了依据。与广泛使用的神经网络方法相比,该方法在样本较少时仍能获得较好的诊断效果,更适用于高压断路器等小样本设备的故障诊断。

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