基于小波变换和二叉树结构的电能质量扰动分类

针对电能质量扰动分类问题,提出了一种基于小波变换和二叉树结构支持向量机的扰动分类方法。首先,通过交流暂态仿真软件产生8种典型扰动信号和2种复合扰动信号作为样本集;然后,通过小波变换进行多个特征的提取,包括信号在特定频带下的能量和小波系数标准差;最后,通过样本集,对二叉树结构支持向量机分类器进行训练和测试。测试结果表明,该方法能够有效识别常见的10种扰动信号,具有分类正确率高、训练时间短的优点。

Power Quality Disturbances Classification Based on Wavelet Transform and Binary Tree Architecture

A new method based on wavelet transform and support vector machine with binary tree architecture(SVM-BTA) was presented for power quality disturbances classification.At first,by use of alternative transients program(ATP) eight typical and two complex disturbance signals were generated as sample set.Then wavelet transform was applied to obtain multiple features,including signal energy and standard deviation of wavelet coefficients in special frequency band.At last,the SVM-BTA multi-classifier was trained and...