The Application Research Of Intelligent Diagnosis Methods In Power Transformer Fault Recognition

Research of power transformer fault diagnosis methods for the prevention and reduction of power transformer fault occurrence can enhance the safety and reliable power supply level of the transformer,as well as be good for the development plan of the national integrated grid.It has the extremely crucial guide value and significance.Considering the reasons for the characteristics of electric power transformer and on the basis of the current status quo in power transformer fault diagnosis,this paper further studies the diagnosis method of artificial intelligence applications in the field of power transformer fault diagnosis problems.This paper studies the basic methods of fault diagnosis of power transformer-the improved three ratio method and probabilistic neural network method.The advantages and disadvantages of two methods are summarized and analyzed,which lays the foundation for the research of artificial intelligence diagnosis method.Fault diagnosis based on the dissolved gas analysis(DGA)data is the most simple and extensive method for fault diagnosis of power transformer faults.Based on this,new methods for fault diagnosis of power transformers are explored.A fault diagnosis method of power transformer based on fuzzy relations and self-organizing competitive network is studied.The traditional transformer fault diagnosis method and the artificial intelligence network diagnosis method are used to construct the power transformer fault diagnosis method based on the self-organizing competitive network model.A new feasible idea is provided for the real-time online and high reliability diagnosis of transformer fault.The results of case analysis show that this method improves the accuracy of real-time online fault diagnosis of power transformer.A fault diagnosis method of power transformer based on support vector machine with improved particle swarm optimization is proposed.Firstly,the optimization performance of parameters with standard particle swarm optimization(PSO)algorithm and improved particle swarm optimization algorithm are studied respectively.Secondly,based on the theory and research of support vector machine(SVM)and combined with the ability of improved particle swarm optimization algorithm to improve the performance of the parameters,the fault diagnosis model of transformer based on improved particle swarm optimization SVM is established.Finally,the results show that the accuracy andconvergence speed of the power transformer fault diagnosis method based on the improved particle swarm optimization support vector machine are higher than the traditional fault diagnosis method,and it is more suitable for the practical application of power transformer fault diagnosis.