基于小波概率网络的局部放电模式识别

针对高压电器局部放电模式分类中样本数较少,常规的分类方法识别率较低,提出了一种基于概率神经网络与小波变换的混合算法。利用实验室模拟的局部放电信号进行小波分解,提取小波能量系数作为特征参数,并作为概率神经网络的输入进行分类。其得到的结果优于多层前馈神经网络及采用顺序最优化学习方法的支持向量机算法。

Pattern Recognition of Partial Discharge Based on Wavelet Transform and Probabilistic Neural Network

For the small number of samples in the classification of partial discharge pattern in high voltage electrical appliances and the poor recognition rate of conventional classification methods,a mixed algorithm is proposed based on probabilistic neural network hybrid algorithm and wavelet transform.Wavelet decomposition is performed on partial discharge signals in a laboratory simulation with the extracted wavelet energy coefficient as the feature parameter,and as the input of a probabilistic neural network for classification.The obtained results are better than that by the multilayer feedforward neural network (MLP) algorithm and the support vector machine method using sequential learning optimization.