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小波分析是一种优于传统信号分析方法的时频分析方法。由于同时具有时域和频域的良好局部化特性及自动调节时频窗的特点 ,可以聚焦到被分析信号的任意局部细节 ,具有分析效率高、质量好的优点 ,因此近年来被广泛用于信号处理。低压电力网载波通信也是近年来电力系统中的一个热门课题 ,具有许多优点 ,然而由于低压电网噪声成分复杂 ,随负荷变化大 ,具有很强的非平稳特性 ,因此又是一个极具挑战性的课题。文章探索了一种能对低压电网通信信号进行有效处理的方法 ,采用取不同 N值的 Daubechies小波对实际电力系统中采集的几种载波通信信号进行分析计算 ,得出的结论为 :Daubechies小波可以对通过低压电力网进行通信的载波信号进行有效的处理。采用不同 N值的 Daubechies小波可以得到不同的处理效果 ,滤波器的长度越长其滤波性能越好 ,但信号处理的延时也越长 ,因此实际应用时必须综合考虑滤波性能、时延及实际需求等多方面的因素 ,以选择恰当的小波函数
Wavelet analysis is a time-frequency analysis method superior to traditional signal analysis methods. Due to the combination of good localization in the time domain and frequency domain and the automatic adjustment of the time-frequency window, it can focus on any local detail of the signal to be analyzed and has the advantages of high analysis efficiency and good quality. Therefore, it has been widely used in recent years Signal Processing. Low-voltage power line carrier communication is also a hot topic in power system in recent years, which has many advantages. However, because of the complexity of low-voltage power network noise components, large variation with load and strong non-stationary characteristics, it is also a challenging task . In this paper, an effective method to deal with low-voltage power grid communication signals is explored. Several Daubechies wavelets with different N values are used to analyze and calculate several carrier communication signals collected in the actual power system. The conclusion is: Daubechies wavelet can The carrier signals communicated through the low-voltage power network are effectively processed. Adopting Daubechies wavelet with different N values can get different processing results. The longer the filter length, the better the filtering performance, but the longer the delay of signal processing, so the practical application must consider the filter performance, delay and actual Demand and other factors, to select the appropriate wavelet function