摘要
电压暂降对煤矿配电网的安全运行具有严重影响,为了快速准确辨识不同电压暂降源,提出小波熵结合支持向量机的电压暂降源辨识方法,通过小波熵来表征不同电压暂降信号,采用支持向量机对不同电压暂降信号的特征向量进行自动分类辨识。结果表明:小波熵特征能够有效地表征3类不同电压暂降源信号,实现对电压暂降信号快速辨识。
Voltage sags have a serious impact on the safe operation of the coal mine distribution network, in order to quickly and accurately identify different voltage sags, the identification method of voltage sag source based on wavelet entropy and support vector machine is presented. The different voltage sag signals are represented by wavelet entropy, and the eigenvectors of different voltage sag signals are automatically classified and identified by using support vector machine. The results show that the wavelet entropy feature can effectively represent three types of voltage sag signals, and can quickly recognize the voltage sag signal.
作者
冯晓群
FENG Xiao-qun(State Grid Ningxia Electric Power Company, Yinchuan 750001, Chin)
出处
《煤炭技术》
CAS
2018年第8期238-240,共3页
Coal Technology
关键词
煤矿配电网
电压暂降
小波熵
支持向量机
coal mine distribution network
voltage sag
wavelet entropy
support vector machine
