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A classification method of power quality disturbance based on wavelet packet decomposition

机译:基于小波包分解的电能质量扰动分类方法

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The power quality problems has been given more attention due to the proliferation of sensitive equipments. In order to mitigate the influence, various power quality disturbances must be classified before an appropriate action can be taken. Wavelet packet is developed on wavelet transform, which can provide more time-frequency information. This paper selects the energy and entropy of terminal nodes through wavelet packet decomposition as a feature vector respectively, using the Fisher linear classifier to design piecewise linear classifier in order to classify the disturbances, which are simulated and analyzed. The simulation results indicate that the entropy feature vector has a higher recognition accurate ratio.
机译:由于敏感设备的增殖,电力质量问题更加受到关注。为了减轻影响,必须在采取适当的动作之前对各种电能质量扰动进行分类。小波分组在小波变换上开发,可以提供更多的时间频率信息。本文使用Fisher线性分类器分别为特征向量选择通过小波分组分解作为特征向量的终端节点的能量和熵。为了对模拟和分析的干扰来进行分类,以分类和分析。仿真结果表明熵特征向​​量具有较高的识别准确比。

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