The Design And Implementation Of Fault Monitoring And Early Warning System For Power Equipment

Power equipment is the most important core part of the smart grid, whether the power equipment is normal or not directly influences security and stability of the whole power system. Application development and practical power equipment fault monitoring and early warning system is made in order to protect unexpected power equipment maintenance, make the equipment operation more safe and reliable, improve risk analysis ability, change passive to active prevention, strengthen the power equipment maintenance technology.The system is given priority to the electric power equipment parameter diagnosis, diagnosis is on the basis of reference to the power equipment preventive test procedures. The system diagnoses the comprehensive data in the database, and uses the BP neural network intelligent diagnosis method of identifying the equipment running state and fault, early warning information is given according to the results of the diagnosis.In order to improve the early warning ability of equipment, generators, for example, this paper firstly analyzes the structure and common fault of generator, this paper proposes the methods of using the BP neural network to realize fault symptoms and fault types of corresponding, in detail elaborated the diagnosis process and diagnosis algorithm, and then design the B/S mode of electric power equipment fault monitoring and early warning system based on WEB of the overall architecture, use JSP development technology, using MySQL database design and realization of fault monitoring and early warning system function module, equipment monitoring and fault diagnosis module is realized.