Application Of Data Mining Technology In Power System Fault Diagnosis

With the rapid development of information technology,the application of computer technology in all walks of life,the vast amount of information into all aspects of people,people are now in an era of information explosion.How to deal with the massive data,how to find the valuable data,has become the focus of the research.In the electric power industry,more and more electric power equipment,power grid structure is becoming more and more complex,how to network data collected through the extraction and analysis of operation,get valuable diagnostic information,data mining technology to the processing and analysis for power system fault diagnosis in the amount of information provided.In this paper,we apply the data mining technology to the fault diagnosis of power system,and build the model of power system fault diagnosis.In this model,the decision tree is used to combine the knowledge acquisition and representation.In the power system fault diagnosis model,we improve the decision tree algorithm in data mining technology,and use it to complete the acquisition and integration of knowledge.The system is composed of four modules: inference engine,interpreter,decision tree algorithm and graphical interface.The main function of inference is inference of decision tree algorithm to generate the rules of inference interpreter returned by rules and decision tree or expert input rules,decision tree algorithm,the main role is to build a high efficient and easy-to-use decision tree and composition of precise rules for the inference machine,a graphical interface for display output directly.The experimental system using the.NET platform architecture,the system can also expand the application of data samples or use data mining algorithms to deal with other aspects of the problem.