Main shaft instantaneous azimuth estimation for wind turbines
• Novel method and algorithm for the tacholess estimation of the instantaneous azimuth in wind turbines. • The algorithm only requires the tangential acceleration and the axial speed measured by an IMU placed on the main shaft. • The algorithm is robust and works on any operation regime of the wind turbine. • The estimator is insensitive to misalignments in the sensor, and independent of the shaft diameter. • The algorithm, based on the dynamic model of the rotation, is suitable to be implemented in real time with an IMU sensor. We present a novel approach to estimating the instantaneous main shaft angular position in the context of wind turbine structural health monitoring. We show that only two IMU channels – gyroscope axial and accelerometer tangential – contain enough information to build an acceleration state-space model that properly captures the rotational dynamics of a wind turbine. The kernel of the model is an in-phase and quadrature time-varying sinusoid whose argument is driven by the integral of the gyroscope output. This approach clearly stands in contrast to most state-of-the-art methods, where the gyroscope output is explicitly modeled. The model equation describes the states dynamics, which simultaneously assesses the instantaneous amplitude and initial phase of the angular displacement through a first-order autoregressive process. Such a state-space model features only two states per time instant; furthermore, it is linear-in-states and therefore straightforwardly estimated by the linear Kalman filter. It is shown that the instantaneous azimuth estimates obtained from the state-space model, linearly combined with the gyroscope output, effectively cancel out the long-term drift in the estimate. The benchmark results suggest that the proposed method outperforms a state-of-the-art method, in terms of robustness against noise and adaptability to changing operating regimes in a wind turbine.
Authors
- Xabier Iriarte (ORCID: https://orcid.org/0000-0001-8215-1176)
- Miroslav Zivanovic (ORCID: https://orcid.org/0000-0001-8729-6657)
- G. Gainza (ORCID: https://orcid.org/0000-0001-5673-2452)
- A. Carlosena (ORCID: https://orcid.org/0000-0002-7146-4043)
- Aitor Plaza (ORCID: https://orcid.org/0000-0002-4929-1246)
- Iñigo Vilella (ORCID: https://orcid.org/0000-0001-8054-6617)
Institutions
- Universidad Pública de Navarra (UPNA) (ES)
Publication Details
- Journal
- Mechanical Systems and Signal Processing
- Published
- 2025-02-20
- DOI
- https://doi.org/10.1016/j.ymssp.2025.112478
- Citations
- 1
- Primary Topic
- Structural Health Monitoring Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.95
Funders
- Gobierno de Navarra
- Agencia Estatal de Investigación
- H2020 European Research Council