Partial Discharges Pattern Classification in High Voltage Circuit Breakers

2018 2nd International Workshop on Renewable Energy and Development

能源学;经济学

Lu, Yufeng^1 ; Su, Yi^1 ; Wang, Feifeng^1

Electric Power Research Institute of Guangxi Power Grid, Minzhu road 6-2, Nanning, China^1

关键词: Adaptive neuro fuzzy inference systems (ANFIS);    Fuzzy Inference systems (FIS);    High voltage circuit breaker;    High-voltage equipments;    Linear discriminant analyses (LDA);    Partial discharge activity;    Partial discharge measurements;    Prefabricated defects;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/153/4/042046/pdf
DOI  :  10.1088/1755-1315/153/4/042046

来源: IOP

【 摘 要 】

Partial discharge (PD) measurement is among the most important diagnostics methods of insulation systems in high voltage equipment, which makes it convenient to assess the insulation status. Partial discharge activities may stem from various defects, and correspondingly behave differently. Here, the PD patterns produced by 3 different laboratory models representing defects in High Voltage Circuit Breakers are recorded and analyzed. The research aimed at conducting PD tests with three apparatus including prefabricated defects. From the PD pattern data, statistical features were extracted and these features were reduced by linear discriminant Analysis (LDA). Adaptive neuro-fuzzy inference system (ANFIS) was used to train the fuzzy inference system (FIS).The trained FIS was then used to recognize the source of the PDs. Results show thatANFIS classification has a high success rate and highest average success rate at 110kV reaches 95.83%.