An effective Power Quality classifier using Wavelet Transform and Support Vector Machines

作者：

Highlights：

• The method classifies more than one PQ event within the same temporal window.

• The algorithm was based on Wavelet Transform and Support Vector Machine (SVM).

• The classification method uses One vs. One multiclass SVM.

• The algorithm was tested using several real PQ events obtained from the field.

• More than 92% of the measured PQ events were successfully detected and classified.

摘要

•The method classifies more than one PQ event within the same temporal window.•The algorithm was based on Wavelet Transform and Support Vector Machine (SVM).•The classification method uses One vs. One multiclass SVM.•The algorithm was tested using several real PQ events obtained from the field.•More than 92% of the measured PQ events were successfully detected and classified.

论文关键词：Power Quality,Wavelet Transform,Support Vector Machine,Complex disturbance detection and classification

论文评审过程：Available online 8 April 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.04.002