电压暂降的改进S变换分析与分类

Detection and Classification of Voltage Sags Based on Modified S-transform

提出了一种采用改进S变换(MST)检测和识别电压暂降的方法.推导了白噪声在S变换和MST下的平均功率谱,证明了改进S变换对噪声具有抑制作用.分析了改进S变换中可变参数的选择思想,给出了MST提取暂降幅值、暂降时刻和相位的方法.利用MST变换分析短路故障、感应电机启动和变压器空载激磁3种扰动源引起的电压暂降信号,并提取6种电压暂降特征参数,形成分类判决规则对暂降源进行识别.仿真结果表明,改进S变换比S变换提取的电压暂降幅值和暂降时间更加精确,MST提取的特征量能全面明显地反映扰动源特征,分类算法能够实现对3种暂降扰动源的正确识别.

A new approach based on modified S-transform（MST） was proposed to detect and classify the voltage sags.The average power spectrum of white noise was deduced on the S transform and MST,and the results showed the MST＇restraint upon noise.The selection thinking of adjusting parameter in MST was described,the method to get the amplitude was obtained,and the time and phases of the sag were given.Then the voltage sags in short-circuit fault,induction-motor starting and transformer exciting without load were analyzed,six feature parameters were extracted and decision rules were obtained to recognize the sag disturbance sources.The simulation results show that the amplitude and time of the voltage sags by using MST are more accurate than those by using S transform,and the classification method has a high classification ratio.