Wind turbine generator bearing fault diagnosis method under variable speed

Abstract

The invention discloses a wind turbine generator bearing fault diagnosis method under the variable speed. According to the method, a rotation angle change curve is drafted according to the bearing rotation speed; equal angle division for the rotation angle change curve is carried out, and an equal angle re-sampling time sequence is determined; interpolation for a bearing vibration signal is carried out according to the time sequence, a random Gauss white noise sequence is added to an angle domain vibration signal, and the signal added with the white noise is processed by utilizing an empirical mode decomposition (EMD) algorithm to acquire multiple sets of IMF; a kurtosis value of each IMF component is calculated; the IMF with the largest kurtosis value is selected and taken as a sensitive IMF; Hilbert envelope demodulation for the sensitive IMF is carried out to obtain an envelope signal, the envelope signal is processed by utilizing Fourier transform to obtain order envelope spectrum of the sensitive IMF, the fault characteristic frequency is extracted, and fault diagnosis on the wind turbine generator bearing is realized. The method is advantaged in that influence of rotation speed change on vibration signal analysis can be eliminated, and accuracy and validity of fault diagnosis can be improved.

Description

technical field [0001] The invention belongs to the technical field of mechanical equipment fault detection, and relates to a method for diagnosing a wind turbine bearing fault at variable speeds. Background technique [0002] Because most of the wind farms are located in areas with complex and harsh environments, they are often affected by extreme weather. As the accumulative running time of the unit increases, the components of the unit continue to age and are prone to failure. The main shaft, yaw, pitch, generator, gearbox and many other parts of wind turbines are equipped with bearings, and bearing failures account for a high proportion of unit failures. In order to reduce the downtime of wind turbines and reduce the maintenance costs of the wind turbines, it is necessary to monitor the condition of important bearing components of wind turbines. Due to the harsh operating conditions of wind turbine bearings, complex forces, and often affected by alternating loads and i...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a wind turbine bearing fault diagnosis method under variable speed, which solves the problem that the vibration signal of the wind turbine often shows non-stationary characteristics when the speed changes during operation, so that the traditional fault diagnosis method can be used under variable speed conditions. It is difficult to realize the problem of accurate judgment of fault state

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