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

• We propose the autocorrelation-based time synchronous averaging (ATSA).
• Vibration characteristics of planetary gearbox are studied using autocorrelation function.
• A systematic approach is developed to select an optimal size and shape of windows.
• ATSA is data-efficient compared to the conventional TSA for planetary gearbox.
• ATSA helps obtain reliable gearbox diagnostics results with limited stationary data.

We propose autocorrelation-based time synchronous averaging (ATSA) to cope with the challenges associated with the current practice of time synchronous averaging (TSA) for planet gears in planetary gearboxes of wind turbine (WT). An autocorrelation function that represents physical interactions between the ring, sun, and planet gears in the gearbox is utilized to define the optimal shape and range of the window function for TSA using actual kinetic responses. The proposed ATSA offers two distinctive features: (1) data-efficient TSA processing and (2) prevention of signal distortion during the TSA process. It is thus expected that an order analysis with the ATSA signals significantly improves the efficiency and accuracy in fault diagnostics of planet gears in planetary gearboxes. Two case studies are presented to demonstrate the effectiveness of the proposed method: an analytical signal from a simulation and a signal measured from a 2 kW WT testbed. It can be concluded from the results that the proposed method outperforms conventional TSA methods in condition monitoring of the planetary gearbox when the amount of available stationary data is limited.