Wind generator tower vibration fault diagnosis and monitoring based on PCA

Vibration signal is one kind of important variables for wind turbine in Supervisory Control and Data Acquisition (SCADA) System. With modeling and analysis of vibration signals, incipient failure of key components such as tower, drive train and rotor could be detected. In this paper, Principal Component Analysis (PCA) was applied to model the tower vibration providing a good understanding of the tower vibration dynamic characteristics and the main factors influencing these. The merits and physical interpretation of PCA are also discussed and analyzed. With SCADA of one wind turbine during April to June in 2006, PCA model for tower vibration in normal working condition was established and validated. This method monitoring the operation of the wind generator by calculating the monitoring statistic Hotelling T² (T² for short) and SPE. If T² and SPE statistics over confidence limit, the decision system is abnormal. We can calculate contribution rate of each variable on the main component,then get the cause of the fault . Wind generator fault data set simulation verify the effectiveness of the proposed method.