Fast identification of partial discharge sources using blind source separation and kurtosis

A technique for the fast identification of partial discharge (PD) sources is proposed for the detection of mechanical failure or damage to insulation materials by using wireless remote control and monitoring systems in substations. An estimation of the number of PD sources can help to evaluate the insulation performance and lifetime of power equipment. Multiple PD sources can be generated during the operating voltage where their electromagnetic radiations are highly impulsive, non-Gaussian noise and the resulting probability distribution function is heavy-tailed. Multiple PD sources can be estimated by their electromagnetic radiations via blind source separation (BSS) and measuring the excess kurtosis using low-cost wireless intelligent electronic devices. The efficiency and performance of the proposed method is demonstrated by simulating PD sources based on the spatial Poisson point process where the number of sources is a random variable not known by the receiver. Assuming non-white and decorrelated or non-Gaussian and independent sources, results show that the number of significant PD sources can be estimated with low error rate. Underdetermined problems in BSS can affect performances.