Development Of Remote State Monitor And Fault Diagnosis System For Wind Turbine Generators

Wind power is considered as a kind of renewable energy source, and it has been popularized and researched vigorously in recent years all over the world. With increases in a wind turbine unit capacity and install base year by year, how to monitor and diagnose wind turbines has begun to attract people’s attention. Most of wind turbines are located in remote areas with poor working conditions and inconvenient maintenance, which easily leads to damages on wind power installation and have a bad effect on production. Therefore, it is of great significance to develop a remote condition monitoring and fault diagnosis system on wind turbine generators.After a practical investigation of wind farm monitoring system this paper try to develop a set of analysis systems used for remote condition monitoring and fault diagnosis of wind turbines.The developed system regards the wind turbine drive system as a monitoring object, and applies the virtual instrument technology from National Instruments and LabVIEW8.6as a software platform.The paper summarizes the common fault types of wind power generator drive system and their corresponding fault symptoms respectively. And then conventional signal analysis methods and fault diagnosis technologies were introduced to provide theoretical basis for the system development.The paper carried out an integral structure design of remote state monitoring and fault diagnosis system on the wind generator, and then completed the system hardware components selection and overall system interface design, and also determined what kind of monitoring targets and monitoring points and the usage of LabVIEW programming language.This paper finished modules construction of the presented system, including data collection storage module, wavelet de-noising module, signal processing module, feature extraction module and wavelet neural network diagnosis module. The constructed system modules can achieve functions covering with a wind turbine vibration signal preprocessing, feature extraction, remote monitoring and fault diagnosis, which would provide much help for fault feature extraction and fault diagnosis.In addition, the paper still applied Remote technology and Data Socket technology to the established system to make a remote monitoring function come true by use of the strong network communication function of LabVIEW. It can be concluded that the developed wavelet neural network diagnosis system help increase the accuracy of the constructed remote monitoring and fault diagnosis system of wind turbine.