Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published June 18, 2018 | public
Book Section - Chapter

Structural Identification for Dynamic Strain Estimation in Wind Turbine Towers

Abstract

Fatigue is a common issue in steel structures such as wind turbine towers, which is caused by cyclic wind and wave excitations. Therefore, estimation of the remaining fatigue life of the structural and foundation system is of concern. For this purpose, continuous monitoring of the structure is necessary to obtain strain data at fatigue critical points. Since installing and maintaining strain sensors in critical underwater location is difficult, strain data is often available only from a few sensors at accessible locations. Using these sparse sensors, the strain time histories at fatigue critical points can be estimated using estimation techniques. These techniques can identify the structural system using limited measured response data and a system model. In this paper, we implement a model updating approach followed by modal expansion to estimate the strain time history at critical points in a numerical case study representing an offshore wind turbine tower. The acceleration response of the structure is simulated using a finite element model and polluted with Gaussian white noise to represent measurements. The measurements are then used for model updating and strain estimation. The accuracy of the methods and their robustness to the measurement noise and model uncertainty are investigated. The estimated strain response time histories can later be used as input to an appropriate fatigue damage model to estimate the current state of fatigue damage in the system.

Additional Information

© 2019 The Society for Experimental Mechanics, Inc. First Online: 12 June 2018. Partial support of this study by the National Science Foundation Grant 1254338 is gratefully acknowledged. The opinions, findings, and conclusions expressed in this paper are those of the authors and do not necessarily represent the views of the sponsors and organizations involved in this project.

Additional details

Created:
August 21, 2023
Modified:
January 15, 2024