Abstract: In order to evaluate the porcelain post insulator of substation effectively. An analysis method of vibration signal characteristics and fault diagnosis of porcelain post insulator based on the combination of local mean decomposition (LMD), principal component analysis (PCA) and sample entropy is proposed. Firstly, the diagnosis signal of porcelain post insulator is decomposed into local mean value, and then the PF component (the component with physical significance of instantaneous frequency after LMD decomposition) is obtained, Secondly, the sample entropy is calculated as the eigenvector to represent the state of porcelain post insulator, and SVM is used to train the input vector, Finally, the feature vector of the test sample is input into the trained SVM for classification and recognition. The results show that the method can effectively extract the fault features of porcelain post insulator and accurately and quickly realize the fault classification.