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.

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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

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article

Main shaft instantaneous azimuth estimation for wind turbines

Xabier Iriarte, Miroslav Zivanovic, G. Gainza, A. Carlosena et al.
1 citations
Mechanical Systems and Signal Processing
Structural Health Monitoring Techniques
0.95
article

Main shaft instantaneous azimuth estimation for wind turbines

Xabier Iriarte, Miroslav Zivanovic, G. Gainza, A. Carlosena, Aitor Plaza, Iñigo Vilella
article en
1 citations

Abstract

• 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.

Mechanical Systems and Signal ProcessingVol. 228
Universidad Pública de Navarra (UPNA) (ES)
Gobierno de Navarra, Agencia Estatal de Investigación, H2020 European Research Council
Affordable and clean energy
Openalex Percentile: Top 29%
Structural Health Monitoring Techniques
0.95
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