Partial discharge noise comparison and recognition method based on multi-channel smooth decoherence algorithm applied to GIS

Abstract In order to further improve the accuracy of the online monitoring spectra of partial discharge in gas insulated switchgear, a partial discharge distributed monitoring system is studied, and distributed sensors are used to simultaneously obtain ultra-high frequency electromagnetic wave signals. Based on the accumulated partial discharge spectra of each sensor, the smooth decoherence noise recognition algorithm is proposed on a long-term cumulative spectral pattern, which is used to analyse the correlation between the spectra of each sensor. Furthermore, a method for determining whether partial discharge is an internal signal is proposed, and its effectiveness is verified by practice, the results confirmed that the algorithm can avoid the misjudgement of partial discharge results caused by distributed sensor interference.