Exploration of Power Fault Classification System Based on Transformer
The distribution system is susceptible to external environmental influences.Classifying potential failure risks in time and space is crucial for developing maintenance and overhaul plans for the distribution system to improve the reliability of the entire distribution system.A dynamic classification model for distribution system fault risk based on Transformer model and attention mechanism is proposed to address the problem of imbalanced spatiotemporal distribution of distribution system data.The aim is to predict the fault results,causes,and locations,and conduct a comprehensive analysis based on multiple feature attributes.The experimental results show that the model performs well in different fault classification tasks,especially in capturing the faults caused by natural factors,showing the significant advantages.This study not only further confirms the crucial role of self-attention mechanism and position encoding in improving model per-formance,but also fully demonstrates their practical value in data analysis of distribution systems.
distribution systemfault riskclassification modelTransformer model
万方数据
维普
