Research on Intelligent Monitoring and Fault Diagnosis Technology in Electric Power System
This research focuses on data-driven fault detection methods,especially Principal Component Analysis(PCA)and Support Vector Machine(SVM).PCA extracts key features by dimensionality reduction,while SVM realizes fault classification by constructing hyperplane.On this basis,the application of condition monitoring and predictive maintenance,fault self-healing and system recovery is discussed emphatically,and the effectiveness of these measures is verified by simulation experiments.The results show that these methods can significantly improve the accuracy of fault detection and provide strong support for the reliable operation of power system.
万方数据
维普
