The Research of Wind Turbine Condition Monitoring Based on ANFIS

Shuang-xi ZHAO, Cheng XIAO, Li-jun HOU, Xia YANG, Lei ZHANG, Xin-zhu LI


With the continuous development of wind power industry, the number of installed wind power generator is increasing. Due to its complicated structure and poor working conditions, easily happened all kinds of faults. For the nonlinear problems and difficulty in modeling of wind turbine system fault diagnosis , this paper proposes a wind turbine monitoring system, using 20 different SCADA normal data developed 20 adaptive fuzzy neural inference system (ANFIS) model, and proposes a kind of can apply to all models of anomaly detection method, using the prediction error to evaluate the practicability of model in a simulated SCADA signal, comprehensive 20 anomaly detection results of the model, get the final decision to the conclusion that the simulation results show that the system can accurately diagnose the wind turbine system fault.


Wind turbine, Condition monitoring, ANFIS


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