Study And Application Of The Fault Diagnosis Information Method Of Large-Scale Wind Turbine's Transmission System

Energy and environmental is the human survival and development problems which is urgent to solve. Wind energy is a renewable clean energy, which is in the key development to the countries around the world, and the key of the development is to convert wind power to electricity via wind turbine. Now the development of wind turbine is tending to more large-scale.In order to enhance the level of wind energy applications and wind turbine operations , especially prevent the vast economic losses and casualties caused by emergency or gradient fault, the operational status of equipment should be monitored in real time, and fault warning and fault diagnosis are necessary. By these revenue losses will be minimized. The fault rate of transmission system is high among all the common faults of wind turbine. This paper simply introduces the common fault of transmission system, and makes a general description of fault diagnosis technology.In the process of wind turbine fault diagnosis, the paper mainly studies the information analysis method from simple to complex fault diagnosis methods. To achieve intelligent diagnosis, the theory of BP artificial neural networks is introduced in the paper, which is used to distinguish the conditions of the large-scale wind turbine combining with the testing data of the wind power simulation platform, and then achieve fault warning and multiple faults'type discrimination. According to the fault information, combined with the evidenced information, the bayesian network fault diagnosis method is studied in the paper, which is based on probability to determine fault types, and the establishment of different network to locate fault location. Based on bayesian networks fault diagnosis method, fault diagnosis system of wind turbine transmission system will be constructed. Through the software programming, a prototype system of fault diagnosis was developed.