Preprints
https://doi.org/10.5194/wes-2022-75
https://doi.org/10.5194/wes-2022-75
27 Jan 2023
 | 27 Jan 2023
Status: this preprint has been withdrawn by the authors.

Regression-based Main Bearing Load Estimation

Amin Loriemi, Georg Jacobs, Vitali Züch, Timm Jakobs, and Dennis Bosse

Abstract. The premature failure of wind turbines due to unknown loads leads to a reduction in competitiveness compared to other energy sources. Especially the failure of main bearings results in high costs and downtimes, as for an exchange of this component the rotor needs to be demounted. Load monitoring systems can make a significant contribution to understand and prevent such failures. However, most load monitoring systems do not take into account the main bearing loads in particular as there is no commercially applicable measuring system for this purpose. This work shows how main bearing loads can be estimated using virtual sensors. For this purpose, several regression models are trained with test bench data considering strain and displacement signals. It is investigated with which combination of signal type and regression model the highest accuracy is achieved. The results show that for either using strain or displacement signals an appropriate accuracy can be achieved. In particular, it is shown that a linear regression with interactions already achieves good accuracy and that further increases in regression model complexity do not add significant value.

This preprint has been withdrawn.

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Amin Loriemi, Georg Jacobs, Vitali Züch, Timm Jakobs, and Dennis Bosse

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2022-75', Anonymous Referee #1, 01 Feb 2023
  • RC2: 'Comment on wes-2022-75', Edward Hart, 13 Feb 2023

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2022-75', Anonymous Referee #1, 01 Feb 2023
  • RC2: 'Comment on wes-2022-75', Edward Hart, 13 Feb 2023
Amin Loriemi, Georg Jacobs, Vitali Züch, Timm Jakobs, and Dennis Bosse
Amin Loriemi, Georg Jacobs, Vitali Züch, Timm Jakobs, and Dennis Bosse

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This preprint has been withdrawn.

Short summary
In the last decades, the size of wind turbines has continuously increased. The increasing rotor diameter results in higher loads acting on the main bearings of wind turbines. In this study, it is discussed how these loads can be estimated using accessible sensor signals and regression models. Therefore, measurement data has been acquired on a full-scale wind turbine test bench. It is shown that linear regression using displacement signals provides good accuracy in estimating main bearing loads.
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