一种电子式电流互感器信号畸变识别方法与应用

Recognition of Electronic Current Transformer's Signal Distortion and Its Application

针对智能变电站中电子式互感器的渐变故障和突变故障,提出一种能够同时识别多种故障信号的算法.首先利用小波变换模极大值理论识别故障信号的奇异点,然后求得信号的Lipschitz指数、小波能量系数、均值差,构成故障信号的特征空间.根据随机生成的500个故障信号样本在特征空间的分布,形成故障信号的诊断模型.仿真实验及实际应用测试表明该算法是有效可行的.

Aiming at the gradual and abrupt faults of electronic transformer in an intelligent substation, this paper presents an algorithm that can identify multiple fault signals simultaneously. Firstly, the fault signals＇ singular points are identified using the theory of wavelet transform modulus maxima, and then the Lipschitz exponent, wavelet energy ratio and mean difference are calculated to constitute a feature space of fault signals. According to the distribution of 500 randomly generated fault samples in the feature space, diagnosis model is formed. Simulation results show that the proposed algorithm can effectively identify several distorted signals such as fixed deviation, ratio deviation and drift deviation simultaneously. The simulation and application in practice substation proves the effectiveness of proposed approach.