Dynamic force reconstruction techniques from incomplete measurements

Jayalakshmi, V.; Lakshmi, K.; Rao, A. Rama Mohan

doi:10.1177/1077546317752709

Cited by 14 publications

(5 citation statements)

References 38 publications

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“…The first method allows the reconstruction of the dynamic loads applied to the structure. Many algorithms for force identification can be found in the literature [33][34][35], which already had practical applications in wind turbines. Fritzen in his works adopted a robust observer technique for estimating the wind loads on a 5 MW wind turbine [36].…”

Section: Extrapolation Of the Bending Moments To Non-instrumented Sec...mentioning

confidence: 99%

Fatigue Assessment of Wind Turbine Towers: Review of Processing Strategies with Illustrative Case Study

et al. 2022

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Wind turbines are structures predominantly subjected to dynamic loads throughout their period of life. In that sense, fatigue design plays a central role. Particularly, support structure design might be conservative with respect to fatigue, which may lead to a real fatigue life of considerably more than 20 years. For these reasons, the implementation of a fatigue monitoring system can be an important advantage for the management of wind farms, providing the following outputs: (i) estimation of the evolution of real fatigue condition; (ii) since the real condition of fatigue damage is known, these results could be an essential element for a decision about extending the lifespan of the structure and the possibility of repowering or overpowering; and (iii) the results of the instrumented wind turbines can be extrapolated to other wind turbines of the same wind farm. This paper reviews the procedures for calculating the fatigue damage of wind turbine towers using strain measurements. The applicability of the described procedures is demonstrated with experimental data acquired in an extensive experimental campaign developed at Tocha Wind Farm, an onshore wind farm located in Portugal, exploring the impact of several user-defined parameters on the fatigue results. The paper also includes the description of the data processing needed to convert raw measurements into bending moments and several validation and calibration steps.

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Section: Extrapolation Of the Bending Moments To Non-instrumented Sec...mentioning

confidence: 99%

Fatigue Assessment of Wind Turbine Towers: Review of Processing Strategies with Illustrative Case Study

et al. 2022

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“…Therefore, an indirect measurement method was proposed by Bartlett and Flannelly in 1979, and it was successfully applied to measure the lateral and vertical hub loads of a helicopter (Bartlett and Flannelly, 1979). The successful example shows the applicability of the indirect measurement method, so the indirect measurement method attracts more and more attentions in engineering applications (Aucejo and De Smet, 2018, 2020; Jayalakshmi et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

The determination of the regularization parameter based on signal-to-noise ratio in load identification

Tang

Zhang

Zan

et al. 2022

Journal of Vibration and Control

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Tikhonov regularization is frequently used to solve the ill-conditioned inverse problem in load identification, and the regularization parameter which plays a significant role in Tikhonov regularization is usually determined by L-curve method. However, two corners appear on the L-curve at some situations, which cause the L-curve method to fail to determine a proper regularization parameter. To improve the accuracy of load identification, a new form of regularization parameter which is based on the largest singular value of the impulse response function matrix and signal-to-noise ratio is developed, and a modified L-curve is plotted. When the norm of the solution and the norm of the residual are balanced, a proper regularization parameter is determined through the modified L-curve. Both simulation and experimental results show that the identified load by the modified L-curve is closer to the actual load than L-curve. It also reveals that the modified L-curve is reasonable and the new regularization parameter is correct, and the accuracy of load identification is improved effectively.

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“…The responses of the passive components (e.g., displacement, acceleration, and dynamic strain) are relatively easy to obtain. Therefore, the load identification methods based on responses have been widely studied and applied (Deng and Cai, 2010, 2011; Jayalakshmi et al, 2018; Meli and Pugi, 2013; Thite and Thompson, 2006; ). Deng and Cai (2010, 2011) showed that the dynamic interaction forces can be identified from the acceleration responses with the superposition principle and influence surface concept, and the effectiveness of this method was verified by an experiment.…”

Section: Introductionmentioning

confidence: 99%

Load identification with regularized total least-squares method

Tang

Zhang

et al. 2021

Journal of Vibration and Control

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Load identification in structural dynamics is an ill-conditioned inverse problem, and the errors existing in both the frequency response function matrix and the acceleration response have a great influence on the accuracy of identification. The Tikhonov regularized least-squares method, which is a common approach for load identification, takes the effect of the acceleration response errors into account but neglects the effect of the errors of the frequency response function matrix. In this article, a Tikhonov regularized total least-squares method for load identification is presented. First, the total least-squares method which can minimize the errors of the frequency response function matrix and acceleration response simultaneously is introduced into load identification. Then Tikhonov regularization is used to regularize the total least-squares method to improve the ill-conditioning of the frequency response function matrix. The regularization parameter is selected by the L-curve criterion. To validate the performance of the regularized total least-squares method, a load identification simulation with two excitation loads is studied on a plate based on the finite element method and a load identification experiment with two excitation loads is conducted on an aluminum plate. Both simulation and experiment results show that the excitation loads identified by the regularized total least-squares method match the actual loads well although there are errors existing in both the frequency response function matrix and acceleration response. In experiment, the average relative error of the regularized total least-squares method is 13.00% for excitation load 1 and 20.02% for excitation load 2, whereas the average relative error of the regularized least-squares method is 35.86% and 53.09% for excitation load 1 and excitation load 2, respectively. This result reveals that the regularized total least-squares method is more effective than the regularized least-squares method for load identification.

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Dynamic force reconstruction techniques from incomplete measurements

Cited by 14 publications

References 38 publications

Fatigue Assessment of Wind Turbine Towers: Review of Processing Strategies with Illustrative Case Study

Fatigue Assessment of Wind Turbine Towers: Review of Processing Strategies with Illustrative Case Study

The determination of the regularization parameter based on signal-to-noise ratio in load identification

Load identification with regularized total least-squares method

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