Font Size: a A A

The Study Of Condition Monitoring And Intelligent Fault Diagnosis System For Wind Turbines

Posted on:2013-10-18Degree:MasterType:Thesis
Country:ChinaCandidate:D J GuoFull Text:PDF
GTID:2248330374956277Subject:Control Engineering
Abstract/Summary:PDF Full Text Request
Wind turbine operation monitoring and fault diagnosis will be the industry’s growth engine, as the wind turbine numbers increased year by year. Poor working conditions and unstable wind speed lead to the wind turbine easily damaged. Usually the wind farm distributes wide, and the wind turbine is unattended, maintenance of the machine is inconvenience. Therefore the study of wind turbine condition monitoring and fault diagnosis has practical significances to control of the maintenance costs and to optimize the maintenance strategy.The paper analyzes the basic structure and working principle of wind turbine, describes the common failures of wind turbine, and gives diagnostic test parameters for each fault. Characteristic signals of early failure are weak, time-varying and non-stationary. Proposes to use wavelet transform combined with neural network to diagnosis the wind turbine faults.In this paper, proposing use wavelet transform improved by reconstruction to eliminate the frequency aliasing, which usually exist in wavelet transforms. Using BP neural network to identify and locate the various fault conditions of the wind turbine. To reduce the BP neural network structure, selecting the characteristic field and features from each sub-band signals as the input of the network. Design an intelligent diagnosis algorithm which combined wavelet transform with BP neural network. Using the smart algorithm analyzes the failure of generator and converter for the wind turbine, the result of the analysis is accurate.Developed wind turbine condition monitoring and fault intelligent diagnosis system. By connecting to the wind farm SCADA database, the system can show a variety of electrical parameters and status parameters of wind turbines. The system uses the intelligent fault diagnosis algorithm to achieve fault diagnosis for gearbox and generator. The system also has the login privileges configuration, online maintenance upgrade, logging, report printing and other functions.
Keywords/Search Tags:wavelet transform, BP neural network, wind turbine, intelligent fault diagnosis
PDF Full Text Request
Related items