Research On Power Transmission And Transformation Equipment Online Status Analysis And Intelligent Diagnosis System

Power transmission and transformation equipment is an important part of the power grid, its availability and stability has a direct impact on the safe operation of power system. To detect and exclude latent faults is an issue of concern for power grid enterprises. With the rapid development of power industry, on the one hand, the structure of power grid continues to expand, in the meantime, the number of transmission and transformation equipment and user demand for the reliability of power supply are increasing greatly; on the other hand, equipment operating data and test data surge with more informational, so the on-line monitoring and fault diagnosis of their insulation is of great practical for realization of state maintenance.An intelligent fault diagnosis model of transmission and transformation equipment based on case-based reasoning is proposed in this dissertation on the basis of learning from relevant researches home and abroad. Based on the historical operating and on-line monitoring data, then applying the model to mining and analysis the data resources in depth, a transmission and transformation equipment online status analysis and intelligent diagnosis system is established. The major works are summarized as follows.This dissertation proposes an intelligent fault diagnosis model of transmission and transformation equipment based on the deep study of fault diagnosis data-driven theory and technology combined with case-based reasoning. The model analyses problems which need to be resolved in the transmission and distribution equipment fault diagnosis applications. The model makes the variety of data inforrmation of equipments as the core, and provides a new way of thinking of the diagnosis of complex equipment which requires a lot of experience for both the lack of a clear causal relationship.Aimed at the key link for fault diagnosis model based on case-based reasoning, study and solve the problem of model case for the establishment and design of the model of the reasoning process. Applying tne nuclear function technique to the model, construct new nuclear function wnich is sensitive to the local data structure and completely data extraction, and apply the nuclear function to the support vector machine classifier. To lay the theoretical foundation for the proposal of the transmission and distribution equipment fault diagnosis model.Study and solve the problem of power transmission equipment state analysis and intelligent diagnosis system data model. Make the power transmission equipment data as the center, then establish the device information model. On this basis, establish the device status sample library and using support vector machine classifier, classification learning of the case base, establish the equipment fault classification device fingerprint identification, generate fault diagnosis tree and equipment failure fingerprint. Finally, the establishment of the state of case-based reasoning transmission and distribution equipment intelligent diagnosis model and algorithm, provide the method guide for the transmission and distribution equipment fault diagnosis.Against the limitations of a number of transmission and distribution equipment online monitoring system, apply the power transmission equipment status intelligent diagnosis model, then use existing transmission and distribution equipment system data for deep integration, and establish the power transmission equipment online status analysis and intelligent diagnosis system, with integrating the information of operation of equipment inspections, off-line test, live detection to diagnose equipment failures in real-time to improve the fault diagnosis capability and accuracy further. Design the overall framework of the system, then discusses the key technologies of the system, and complete the development of a prototype system.Take a500kV transformer in one province electric power company as the research object, transformer oil dissolved gas analysis results are organized into an example application of power transmission equipment status intelligent diagnosis model, the integration of the base of equipment from different systems and equipment operation, real-time intelligent diagnosis of transformer condition, time to find out the potential failure of the transformer, exclusion may lead to a potential cause of transformer failure to verify the validity of the model of the power transmission device status intelligent diagnosis.