基于形态学的动态电能质量扰动的检测与分类

提出了一种基于数学形态学的动态电能质量扰动检测与分类方法。该方法先对整流信号(取绝对值以后的信号)进行开运算以滤除尖峰噪声,再用长度为1/2工频周期的扁平结构元素进行膨胀运算提取其幅值特性;同时对差变信号进行短扁平结构元素的梯度运算来检测和定位奇异点,克服了以往方法可能漏检奇异点的不足。基于已得到的幅值特性和形态梯度可对五种动态电能质量扰动(电压暂降、暂升、中断、暂态脉冲和振荡)进行分类。仿真结果表明,该方法能够有效地对动态电能质量扰动进行检测和分类。

Mathematical Morphology Based Detection and Classification of Dynamic Power Quality Disturbances

The authors propose a method to detect and classify dynamic power quality disturbances (DPQDs) based on Mathematical Morphology (MM). In this method the opening operation of rectified signal's absolute value is performed to filtrate the spike noise, then the dilation operation of flat structuring element, whose length is one half of the period of power frequency, to extract the magnitude characteristic of the signal; meanwhile, the gradient operation of short flat structuring element to differential signal is performed to detect and locate the singular point, thus the defect of possibly undetecting singular point by traditional methods is remedied. Based on the obtained magnitude characteristic of the signal and the morphologic gradient of the differential signal, five kinds of dynamic power quality disturbances, i.e., voltage sag, voltage swell, voltage interruption, transient pulse and oscillation, can be classified. Simulation results show that the proposed method can effectively detect, locate and analyze dynamic power quality disturbances.