Automatic Fault Detection Method of Partial Discharge in UHV Transformer Based on Improved SVM
In view of the problem of automatic detection of partial discharge faults in UHV transformers,the current methods often carry out real-time verification independently for abnormal areas,which has low efficiency and high error rate.Therefore,an automatic fault detection method for partial discharge of UHV transformer based on improved SVM is proposed.Firstly,the fault characteristics of transformer partial discharge are extracted by multi-level method,the detection efficiency is strengthened,and the multi-level detection fault tree is designed.Then,an improved SVM model is constructed and automatic detection is realized with transfer learning.The test results show that this method has a lower detection error rate,which proves its high efficiency and significant improvement of detection accuracy.
improved SVMultra high voltage transformerpartial dischargefault detectionautomatic detectiondetection method