一种基于线性时频分布和二进制阈值特征矩阵的电能质量分类方法

Power Quality Disturbance Classification Based on Linear Time-Frequency Distribution and Binary Threshold Feature Matrix

从电能质量扰动信号中有效提取扰动特征信息并进行正确分类是电能质量监测分析系统需要解决的重要问题。本文提出了一种基于线性时频分布和二进制阈值特征矩阵的电能质量扰动分类方法。首先结合两种线性时频分布(窗口傅里叶变换和S变换)的优点,提取能够表征信号特点的五个特征并对其进行量化和编码;在此基础上,确立了基于二进制阈值特征矩阵的扰动分类判据,通过将二进制特征与阈值矩阵进行数值比较来判定扰动的类型。对电压暂升、暂降、中断、切痕、振荡、脉冲、谐波、谐波和暂降、谐波和暂升9种常见扰动的仿真分析结果表明该方法有较高的准确率(>99%),证明了所提方法的正确性和有效性。

Extracting the characteristic information of power quality disturbances and classifying them is an important problem that should be solved by power quality monitoring system.Proposed a PQ disturbances classification method based linear time-frequency distribution（windowed Fourier transform and S-transform） and binary threshold feature matrix.Combined the advantages of WFD and ST,the method presents five features and binaries them,constitutes a binary threshold feature matrix,classifies different disturbances through comparing the magnitudes of the binary feature to the binary threshold feature matrix.Simulation results of 9 common kinds of disturbances indicate that the method has good performance of accuracy（99%） and shows the validity and efficiency of the method.