In this paper we propose a novel approach to estimate the torque on a wind turbine gearbox using single-axis high sensitivity DC accelerometers. The torque estimator uses an Augmented Extended Kalman Filter (AEKF), combining physics-based models with measurement data. The accelerometer sensor model is derived by analysing the measurements, leading to the identification of two torque-driven acceleration contributions: acceleration due to force excitation and acceleration due to a change in measurement direction. For the latter, two different sources, with distinct frequency content, are capable of changing the measurement direction. The first source corresponds to rigid body motion ( f < 0.15 Hz ), the second one to ring gear deformation (0.15 < f < 4 Hz ). Using this information, the measured signal can be filtered to target specific acceleration contributions. The first torque estimation approach targets frequencies from 0.15 to 4 Hz and produces a Normalised Mean Absolute Error (NMAE) of 2.12%. The second approach targets frequencies up to 0.15 Hz , and will estimate the rigid body deflection angle. The torque is calculated through a linear identified relation between the rigid body angle and applied input torque. This approach yields an NMAE of 2.59%. This leads to the conclusion that high sensitivity DC accelerometers are a valid option for estimating torque on a wind turbine gearbox. These torque monitoring approaches will pave the way for advanced condition monitoring strategies and the calculation of remaining useful lifetime of the gearbox.
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Smeets et al. (2024) studied this question.
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