基于SVD和PNN的电能质量扰动分析方法Analysis Method of Power Quality Disturbance Based on SVD and PNN
吴凯,施康明
WU Kai,SHI Kangming
摘要(Abstract)：
伴随我国电力需求的快速增长,供电系统出现一系列电能质量问题。针对这一问题,提出一种基于SVD和PNN原理的电能质量扰动分析方法。该方法通过对电压信号进行奇异值分解,得到表征信号有效信息的特征值,组成故障特征向量。并结合概率神经网络构建故障分析模型,进行电能质量扰动诊断,提高供电质量。仿真试验证明了该方法的有效性和可行性。
With the rapid growth of electricity demand in China, a series of power quality problems occur in power supply system. Aiming at this problem, this paper proposes an analysis method of power quality disturbance based on SVD and PNN. The method conducts singular value decomposition(SVD) of voltage signal and obtains the characteristic value of the effective information of the signal to form feature vector of fault.Then probabilistic neural network is used to build failure analysis model to conduct power quality disturbance diagnosis. The simulation results show that the method is effective and feasible.
关键词(KeyWords)：
电能质量扰动;故障诊断;概率神经网络
power quality disturbance;fault diagnosis;probability neutral network
基金项目(Foundation):
作者(Author):
吴凯,施康明
WU Kai,SHI Kangming
DOI: 10.19585/j.zjdl.201804012
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