A Method for Extracting Acoustic Emission Signal Frequency Characteristics of Polluted-insulator Discharge

Experimental studies have shown that Acoustic Emission(AE) signals generated by the polluted-insulator discharge contain information of discharge energy. To extract the frequency characteristics of AE signals in polluted-insulator discharge, algorithm combining the empirical mode decomposition(EMD) and fast fourier transform(FFT) is used. Through a great many of artificial contamination experiments, the AE signals in different contamination discharge stages are collected, and the frequency characteristics can be extracted by the method presented in this article. The results show that the frequency characteristics of AE signals can be effectively extracted by the proposed method, which gives the right corresponding relationship between frequency characteristics and the polluted-insulator corona, partial and arc discharge. It also provides technical support for monitoring the intensity of polluted-insulator discharge and the change of external insulation status. The method for extracting AE signal frequency characteristics proposed in this paper has been applied to on-line monitoring of polluted-insulator external insulation status and good results have been achieved.