A new fuzzy neural network strategy of insulators contamination detection for power system transmission line
The detection of insulators contamination is difficult in power systems because many factors can influence the pollution. The contamination condition of insulators is usually estimated by detecting the root mean square (r.m.s) of surface leakage current via online-monitoring system. It ignores the influence of environmental factors, such as temperature, humidity, etc. As these factors are fuzzy-characterized, a new method based on Fuzzy Neural Network (FNN) is proposed to improve traditional insulation contamination detection. The renewed structure of FNN is put forward. The evaluation of contamination severity of insulators is achieved through FNN, which are trained by the field samples. The results prove the validity of the method proposed in the paper and can be used to eliminate the insulator from flashover fault and improve the condition-based maintenance (CBM).
fuzzy neural network insulators contamination detection