Detection and Classification of Complex Power Quality Disturbances Using Hybrid Algorithm Based on Combined Features of Stockwell Transform and Hilbert Transform

Vishakha Pandya, R. Choudhary, Om Prakash Mahela, Sunita Choudhary
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引用次数: 4

Abstract

This manuscript presents a complex power quality (PQ) disturbances recognition algorithm using hybrid features of signals extracted using Stockwell transform and Hilbert transform. A power quality index is proposed with the help of various complex PQ disturbances are detected effectively. Peak magnitudes of this power quality index are taken as input for decision tree supported by rules to classify the complex PQ disturbances. This algorithm is robust to be incorporated in online PQ monitoring equipments. Effectiveness of proposed algorithm has been established for detecting and classifying the different nature of complex nature PQ disturbances. Study is carried out using MATLAB software.
基于Stockwell变换和Hilbert变换混合特征的复杂电能质量扰动检测与分类
本文提出了一种基于斯托克韦尔变换和希尔伯特变换提取的信号混合特征的复杂电能质量(PQ)干扰识别算法。提出了一种电能质量指标,有效地检测了各种复杂的PQ干扰。将该电能质量指标的峰值值作为决策树的输入,由规则支持决策树对复杂的PQ干扰进行分类。该算法具有鲁棒性,适用于在线PQ监测设备。该算法对不同性质的复杂性质PQ干扰的检测和分类是有效的。采用MATLAB软件进行研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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