Research on State Diagnosis Methods of UHF Partial Discharge Sensors Based on Improved ViT

Abstract

UHF partial discharge sensors are key equipment for substation monitoring, but they are subject to complex multi-physical field stresses in substation applications, which leads to a significantly higher failure rate among UHF partial discharge sensors used in substations compared to other applications. Effective fault diagnosis is of great significance for improving the safety of substations. In this paper, we propose an improved model based on ViT (Vision Transformer), which effectively identifies the local features of the data by designing a sliding window mechanism, and has a good feature extraction capability for the feature library formed by UHF partial discharge sensors. The experimental results show that the diagnostic accuracy of the improved model, based on the ViT model, can reach 97.6%, which can effectively improve classification accuracy and shorten training times compared with the ViT model.