Research on Fault Prediction and Diagnosis Method of High Voltage Power Substation Equipment Based on Machine Learning
With the continuous development of the power system,fault prediction and diagnosis for high-voltage power substation equipment have become increasingly crucial.Traditional fault diagnosis methods often rely on manual experience and regular inspections,but this approach is inefficient and lacks accuracy.In recent years,the rapid development of machine learning technology has provided new insights for equipment fault prediction and diagnosis.This article explores in detail the advantages of machine learning in fault prediction and diagnosis for high-voltage power substation equipment,and conducts in-depth research on fault prediction models and diagnostic methods based on machine learning.Through experimental validation,machine learning models have shown excellent performance in fault prediction and diagnosis,providing strong support for the stable operation of the power system.
machine learninghigh-voltage power substationfault predictionfault diagnosis
NETL
NSTL
万方数据
