Retracted: Research on a General Fast Analysis Algorithm Model for PD Acoustic Detection System: Experimental Research

Nowadays, the acoustic detection (AD) of partial discharge (PD) is widely used for defect diagnosis of gas insulated substations (GIS) in normal operation and factory tests, including the live detection, on-line monitoring, and offline tests etc. In this paper, in order to design and develop a general fast analysis algorithm model for PD acoustic detection (AD) system to make an assistant diagnosis, the characteristic of acoustic emission (AE) signals generated by different artificial defects such as protrusions (corona discharge), floating shield (floating discharge), void in spacer (inner discharge) and bouncing particles are investigated in the HV laboratory. Some meaningful parameters behind the detected AE signals are extracted and discussed with showing the discharge pattern of (Δ t
i
, qi) and (t
i
, q
i
) respectively, which are used to distinguish the background noise, PD phenomena or bouncing particles. The results show that the data generated from the discharge tests of the defect models can be used as a sample library for artificial intelligence learning, which can be processed to form a general intelligent analysis model algorithm for GIS PD acoustic detection.