Discrimination of insulation defects in a Gas Insulated Switchgear (GIS) by use of a neural network based on a Chaos Analysis of Partial Discharge(CAPD)

카오스이론을 이용한 GIS 내부 절연결함 판별

In this work, experimental investigation has been mainly done. For this purpose, UHF sensor has been designed and fabricated to detect the partial discharges produced from the 10 artificial defects introduced into the real scale 70kV GIS mock-up under the high voltage at the well shielded room. And also, in order to verify the applicability of the proposed method at the site, the proposed CAPD (chaos analysis of partial discharge) is combined with spectral analysis method in order to identify the nature of the above 10 defects. The PD pattern recognition of each defect has been fulfilled by applying self developed artificial neural network soft ware. The result shows that the recognition rate is reached to be 80% by newly proposed method while the traditional PRPD analysis method leads us to obtain 41%. In consequence, it can be pointed out that the proposed method seems likely to be applicable to the real GIS at the site.