Spall size estimation for wind turbine pitch bearings: observation, signal processing method and experiments

Abstract

It is essential to continuously monitor the spall size of wind turbine pitch bearings to prevent severe faults and catastrophic failure. In the field of spall size estimation for bearings, an essential step is to extract the entry and impact signals simultaneously. And this would become more difficult when it comes to the wind turbine pitch bearings due to the limited fault signals and heavy noise. In this paper, a coherent procedure is proposed to estimate the spall size for wind turbine pitch bearings. Firstly, the characteristics of entry and impact signals in actual wind turbine pitch bearings are observed to be low-frequency and high-frequency dominated, respectively. On the basis of characteristics analysis, a novel two-stage signal processing method called the wavelet augmented sparse dictionary, is proposed to extract the entry and impact signals, which combines the discrete wavelet transform and sparse representation technique. Finally, the spall size is calculated according to aforementioned extraction and geometric constraints. Results from real-world experiments demonstrate the effectiveness of the proposed method.