A novel automatic pulse segmentation approach and its application in PD-induced electromagnetic wave detection

As one of the most effective detection methods for partial discharge (PD), analysis of the radiated electromagnetic (EM) signals detected by ultra high frequency (UHF) sensor has gained broad attentions. However, the main bottlenecks for this method are probably the massive storage requirements and various noise interferences. Therefore, this paper is focused on investigating a new pulse segmentation technique, which is capable of separating PD pulses from noisy measured data to save the storage space and improve the signal noise ratio (SNR). First, a designed average multi-scale morphological dilate-erode filter (AMMDEF) is developed to obtain the smooth envelope shape of PD pulses. Then, instantaneous phase (IP) of the envelope shape is calculated by the Hilbert Transform (HT) and further smoothed using AMMDEF. Finally, a robust IP based boundary identification criterion (IPBIC) is proposed to accurately extract PD pulses from raw data. Various experiments have been carried out and results show that this method could achieve an average detection error rate (DER) at 0.1375 and an average absolute precision error (APE) at 23.1 ns respectively, even the SNR of signal is as low as 0 dB. Superiority of the developed method over traditional pulse segmentation techniques is also demonstrated.