Wibull分布在识别变压器局部放电中的应用

针对不同局部放电源产生不同幅值分布的脉冲，设计了5种典型的变压器人工缺陷局部放电模型，对来自不同放电源的脉冲幅值分布进行了比较，如电晕放电、沿面放电和内部气隙放电，用Weibull概率函数进行分析，并用最小二乘法对Weibull分布进行参数估计，最后用克莱姆法则对结果进行检验。结果表明，此概率函数与局部放电幅值分布吻合，用Weibull分布的参数值可以识别不同的放电源，在两个或多个放电源混合的情况下，用混合Weibull模型可以分离局放信号，得出每种放电现象幅值分布的参数值和标准平均值，根据这些参数就能量化重叠的局部放电现象。

Application of the Weibull Distribution for the Recognition of Transformer PD Phenomena

The problem of identification of partial discharge phenomena occurring in a transformer insulating system is addressed. Under the assumption that different PD sources can produce pulse of different PD distributions, five typical artificial defects have been designed to compare the PD distributions coming from different sources, such as internal voids, surface and corona discharges. In this aim, Weibull distribution has been introduced to estimate the parameters and the least square methods (LSM) have been used to estimate the parameters. The goodness of fit to a Weibull distribution is checked by the Cramer-von-Mises (CVM) test. It is shown that the probability function fits well the partial discharge height distribution. By this way,different discharge sources can be distinguished. by Weibull parameter. In addition, the recognition of two or more PD phenomena simultaneously active is approached by means of an additive Weibull distribution. It allows quantities related to each of the two or more superimposed PD phenomena to be estimated, according to the Weibull parameters and the standard mean quantities.