GIS Insulation Fault Diagnosis Based on Multi-domain Feature Fusion and Probabilistic Neural Network
At present,GIS insulation monitoring has a high false positive rate.In view of this,the present work studied the internal insulation mechanism of GIS,built the experimental simulation platform,proposed the UHF data format technology with equal phase angle,and realized obvious increase in partial discharge information quantity by adopting short-time energy method for noise filtering.The feature extraction technology of partial discharge data based on statis-tics,time-frequency and other methods was studied,and the machine learning method of probabilistic neural network classifier was used to establish the diagnosis model.The actual diagnosis data results show that the method has high diag-nostic accuracy,and the results have been applied to many projects with good application effect.
万方数据
维普
