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An integrated approach of wavelet-rough set technique for classification of power quality disturbances

机译:小波粗糙集技术在电能质量扰动分类中的综合应用

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摘要

This paper presents an integrated approach of wavelet and rough set theory for the classification of power quality (PQ) disturbances. Further, the number of features and the rules required for proper classification are decided through rough set approach. Moreover, as the proposed methodology can reduce the number of features extracted through wavelet to a great extent, it will indirectly reduce the memory requirement for the classification procedure. Eleven types of PQ disturbances are considered for classification. The simulation results show that the combination of wavelet and rough set theory can effectively classify different power quality disturbances. Since rule based approach is easy to understand and simple to implement, the rough set technique is a good candidate for the classification of PQ disturbances.
机译:本文提出了一种小波和粗糙集理论的综合方法,用于对电能质量(PQ)干扰进行分类。此外,通过粗糙集方法确定适当分类所需的特征数量和规则。此外,由于所提出的方法可以在很大程度上减少通过小波提取的特征数量,因此将间接减少分类过程的存储需求。考虑对11种类型的PQ干扰进行分类。仿真结果表明,小波和粗糙集理论相结合可以有效地对不同的电能质量扰动进行分类。由于基于规则的方法易于理解且易于实现,因此粗糙集技术是用于PQ干扰分类的良好候选者。

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