基于小波和神经网络的电能质量辨识方法

Power quality classification based on wavelet transform and neural network

本文提出一种新的基于小波和神经网络技术的电能质量辨识方法。对各种电能质量信号进行时域、频域和幅值分析,并从小波变换结果中提取与信号时域、频域和幅值量相关的几个特征量来表征不同电能质量信号。将这些特征量作为神经网络的输入可以实现电能质量的辨识。计算结果表明该方法的有效性和准确性。

A new Power Quality (PQ) classification method based on the wavelet transform and artificial neural network is proposed in this paper. Some eigenvalues were extracted from the wavelet transform results of the power quality signals and they are related to the signals time domain, frequency band domain and amplitude information. And these eigenvalues can be used as the input vectors of the artificial neural network to classify the power quality signals effectively. The efficient and validity of this method is verified by the calculation results.