基于提升小波和Hilbert变换的暂态电能质量检测

A Lifting Wavelet and Hilbert Transform Fusion Method for Transient Power Quality Detection

  • 摘要: 针对暂态电能质量检测中信号扰动的准确定位和快速类型识别的需求,提出了一种提升小波和Hilbert变换融合的暂态电能质量检测方法.该方法首先利用提升小波在检测信号扰动方面的优越性,通过一层提升小波变换得到信号的近似成分<i<A</i<<sub<1</sub<与细节成分<i<D</i<<sub<1</sub<,然后运用Hilbert变换计算出两种成分的瞬时幅值,根据幅值特性实现对信号扰动时刻的准确定位和对扰动类型的快速识别.仿真与实验表明,所提出的检测方法对扰动时刻定位准确率达到95.7%,对扰动类型识别准确率达到91.8%,与目前使用分类器的方法相比,所提方法具有无需训练、适应性强、实时性好等特点.

     

    Abstract: In oeder to improve the location accuracy and the type identification speed of disturbance in the transient power quality detection, a lifting wavelet and Hilbert transform fusion method was proposed in this paper. Firstly, the lifting wavelet was employed to get signal approximation components <i<A</i<<sub<1</sub< and detail components <i<D</i<<sub<1</sub< from the disturbed signals. And then, the Hilbert transform was used to calculate the instantaneous amplitude of the two components. According to the instantaneous amplitude, the disturbance time and type were identified accurately. Simulation and experiment results show that, the disturbance time location accuracy can reach 95.7% and the type identification accuracy can reach 91.8% based on the proposed method.

     

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