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An integrated approach of Wavelet-Rough Set technique for classification of power quality disturbances

机译:小波粗糙集技术的集成方法,用于电能质量障碍分类

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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:本文介绍了对电能质量(PQ)干扰分类的小波和粗糙集理论的综合方法。此外,通过粗糙的设置方法决定适当分类所需的特征数和规则。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的数量,因此它将间接地降低分类过程的存储器要求。考虑了11种PQ扰动进行分类。仿真结果表明,小波和粗糙集理论的组合可以有效地分类不同的电能质量障碍。由于基于规则的方法易于理解和实现简单,因此粗糙集技术是PQ扰动分类的好候选者。

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