基于小波包多尺度分析的多时间窗行波相关法

为解决行波相关法中时间窗宽度不固定影响故障测距可靠性的问题,提出了一种基于小波包多尺度分析的多时间窗行波相关法。首先,利用最大相关系数选取最优小波基,使得小波包滤波效果达到最佳;其次,以最优小波基为基底将故障信号进行小波包的多尺度分解和重构,由于小波包自身的变换特性,重构后的正反向行波初始波头的宽度随着尺度的增大逐渐变宽,将初始行波波头宽度作为行波相关法的时间窗宽度,此时行波相关法成为一个多时间窗的相关算法;最后,将经包络线处理的单极性正反向行波进行相关算法故障测距。多次仿真分析表明,所提方法消除了时间窗不固定对测距结果的影响,且在不同的故障距离和过渡电阻下均适用。

Research on Traveling Wave Correlation Method Based on Wavelet Packet Multi-scale Analysis

In order to solve the problem that the time window width of traveling wave correlation method is not fixed, a multi-time window traveling wave correlation method is proposed based on wavelet packet multi-scale analysis. Firstly, the best wavelet basis is selected by the maximum correlation coefficient, so that the best effect of wavelet packet filtering is achieved. Secondly, the wavelet packet is decomposed and reconstructed based on the optimal wavelet basis, because of the transformation characteristics of wavelet packets. The width of the reconstructed traveling wave head becomes wider with the increase of the scale, and the width of the initial traveling wave head is taken as the time window width of the traveling wave correlation method. At this time, the traveling wave correlation method becomes a multi-time window correlation algorithm. Finally, the algorithm of fault location is processed based on the algorithm of monopole and forward traveling wave. Simulation results show that the proposed method eliminates the impacts of time window uncertainties on the ranging results, and is applicable to different fault distances and transition resistances.