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Implementation of a Power Quality signal classification system using wavelet based energy distribution and neural network

机译:基于小波能量分布和神经网络的电能质量信号分类系统的实现

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摘要

This paper presents a classification system based on Wavelet Transform for normal Power Quality disturbances. The parameter used for the classification algorithm was energy distribution of detailed coefficient of Wavelet Transform up to 10 leveles of decomposition. Wavelet Transform parameters are effective in classification of disturbance waveforms. Artificial Neural Network was used for the classification purpose which gave satisfactory results. And the algorithm developed in MATLAB was interfaced with Data Acquisition devices to check its accuracy for online classification purpose.
机译:本文提出了一种基于小波变换的正常电能质量扰动分类系统。用于分类算法的参数是小波变换的详细系数的能量分布,最多可分解10个级别。小波变换参数在扰动波形分类中很有效。使用人工神经网络进行分类,结果令人满意。然后将在MATLAB中开发的算法与数据采集设备接口,以检查其准确性以进行在线分类。

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