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Hybrid Methods for Fast Detection and Characterization of Power Quality Disturbances

机译:电能质量扰动快速检测和表征的混合方法

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In this paper, recently developed variants of wavelet transform, namely the maximum overlapping discrete wavelet transform and the second-generation wavelet transform, are used for detection of ten types of the power quality (PQ) disturbance signals. Further, the features of PQ signal disturbances are extracted using these wavelet transforms. Those extracted features are then used to classify various PQ disturbances. Random forest (RF) classifier is presented in this paper. The RF is constructed with multiple trees for classification of large number of classes simultaneously. In order to represent realistic situation, the proposed technique is tested with noisy data...
机译:在本文中,最近开发的小波变换变体,即最大重叠离散小波变换和第二代小波变换,用于检测十种类型的电能质量(PQ)干扰信号。此外,使用这些小波变换可以提取PQ信号干扰的特征。然后将那些提取的特征用于对各种PQ干扰进行分类。本文提出了随机森林(RF)分类器。 RF由多个树构成,用于同时对大量类进行分类。为了代表现实情况,对提出的技术进行了噪声数据测试。

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