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An automatic fault diagnosis method for the wind turbine generator system (WTGS) driven by vibration signal is proposed in this paper. In this method, the vibration signal is used to drive the notch filter network directly, and the frequency selection characteristics of the notch filter are used to extract the fault feature frequency of WTGS components. Then, the extracted fault feature frequency is encoded and a neural network classifier is used to achieve the automatic fault diagnosis of WTGS. In addition, the vibration intensity is calculated to evaluate the fault degree of the WTGS. The innovation of this paper is that the fault feature frequency of the WTGS is derived from parameters of the notch filter rather than the vibration signal itself. The practical on-site application shows the effectiveness of the proposed method, which is of great significance for improving the efficiency of fault diagnosis of WTGS and realizing the batch diagnosis of the fault of WTGS.

Automatic Fault Diagnosis Method for Wind Turbine Generator Systems Driven by Vibration Signals