Autocorrelation-based time synchronous averaging for condition monitoring of gearboxes in wind turbines

Abstract

This paper introduces an innovative autocorrelation-based time synchronous averaging (ATSA) method designed to extract periodic features from vibration signals for the condition monitoring of wind turbine gearboxes, even in the absence of rotational speed data. The proposed method estimates the average rotational speed of the high-speed gear shaft and identifies reference points in the vibration signal, which correspond to specific angular positions of the gear shaft. A comprehensive procedure is developed to implement this method, enabling effective condition monitoring without relying on rotational speed data. The effectiveness of the ATSA method is validated using both healthy and faulty vibration data from wind turbine gearboxes, and a comparison study with phase demodulation and time-frequency analysis methods highlights its advantages.