Identification of two simultaneous partial discharge sources in an oil-pressboard insulation system using acoustic emission techniques

Abstract

Insulation failure is one of the major causes of catastrophic failure of transformers. It is established that partial discharge (PD) causes insulation degradation and premature failure of insulation. In power apparatus, more than one PD source may be active simultaneously. The nature of insulation degradation for multiple PD sources is different from that due to single PD source. Therefore, it will be helpful for severity assessment of insulation degradation, if the number of active PD sources are identified and classified. This paper presents a method for identification and classification of two simultaneously active PD sources using acoustic emission techniques. The acoustic emission (AE) signals are measured for laboratory simulated PD in an oil-pressboard insulation system for three different electrode systems. The measurements of partial discharge acoustic emission (PDAE) signals are carried out for single PD source and for two simultaneous PD sources. The measured signals are analyzed using discrete wavelet transform (DWT), box counting fractal dimension and lacunarity. Box counting fractal dimension and lacunarity are calculated for DWT decomposed signal of major frequency band. Energy distribution in different frequency bands of DWT decomposed signal along with box counting fractal dimension and lacunarity is used for classification of two simultaneous PD sources.