基于MUDW的电能质量扰动定位研究

电能质量检测中的扰动信号具有随机、不规则和多变等特性,使信号识别较为困难,本文通过改进原有的形态非抽样小波(morphological undecimated wavelet, MUDW),将其应用到电能质量检测中,从而对扰动信号进行定位。改进的形态非抽样小波包含广义开闭和闭开混合滤波器以及能定位扰动信号边缘的多分辨形态梯度,该方案满足信号重构条件。利用MATLAB软件,对于含有暂态或稳态的单一和复合扰动信号进行仿真。通过与文献中的形态非抽样小波对比,结果表示改进后的形态非抽样小波有较好的抗噪性能以及识别能力。

Research of Power Quality Disturbance Location Based On MUDW

There are random and irregular and variable properties in power quality disturbance detection signal that make it more difficult to identify the signal. This paper improved the original form of morphological un-decimated wavelet decomposition (MUDW) and applied it to power quality detection to locate the disturbance signals. The improved MUDW scheme contains broad open-close or close-open filter and morphological gradient which detect mutations on the top and bottom edges of signal. The scheme meets the signal reconstruction conditions. This scheme used MATLB to detect transient or steady state with single or composite disturbance signals and compared with the existing form of sampling wavelet. The result shows that the new MUDW scheme can recognize and detect the signal and has good anti-noise performance.