| 06 Nov 2025
Damage identification on a large-scale wind turbine rotor blade using sample-based deterministic model updating
Abstract. Wind turbine rotor blades are among the most critical components of wind turbines, with their structural integrity directly affecting reliability, lifetime, and maintenance costs. Reliable damage identification is therefore essential for structural health monitoring (SHM) strategies in wind energy applications. In this context, the updating of numerical models represents an established method for vibration-based non-destructive damage identification, including damage detection, localization and quantification. Naturally, the model-updating process is affected by different sources of uncertainty. On the one hand, the numerical model always represents an idealization that introduces unavoidable discrepancies between its basic assumptions and reality. On the other hand, the measurement data and identified modal parameters, typically serving as damage-sensitive features, are subject to uncertainty. Despite extensive research on uncertainty quantification and propagation in model updating, comparative studies of model-updating procedures applied to large-scale structures, particularly wind turbine rotor blades, remain scarce. Moreover, the level of model fidelity and the impact of different design variable configurations associated with the selected numerical model are seldom examined in the context of model updating, typically formulated as an optimization procedure.
This study addresses this gap by systematically evaluating how model fidelity and design variable parameterization influence the model-updating results while considering uncertainty associated with the measurement data and identification process. The investigations are conducted using measurement data from a 31 m rotor blade subjected to edgewise fatigue loading. A comparison of the results shows that all design variable configurations yield consistent results, confirming the robustness of the presented model-updating procedures. Model fidelity, however, strongly influences the outcomes, with higher accuracy and detail leading to distinctly improved damage identification.
Competing interests: Raimund Rolfes is a member of the editorial board of the wind energy science journal.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
In their manuscript submitted for publication in Wind Energy Science, the authors present a study of fatigue damage identification for a wind turbine rotor blade. The blade is a specimen of 31 m long which was tested in the lab and subjected to cyclic edgewise loading in order to generate (realistic) fatigue damage. During the test, the blade was instrumented with accelerometers to monitor changes in modal parameters resulting from the fatigue damage. Three states of the blade are considered in the damage identification which occurs through the updating of a finite element model of the blade. A beam as well as a shell model of the blade are used, where damage is represented as a reduction in stiffness in a zone of the blade, considering different damage parameterizations. As on objective function, a fit of the difference in modal properties between two (of the three) states is considered rather than tuning the model to each distinct state and subsequently checking the difference in parameters. Statistical uncertainty in the estimated modal characteristics is considered by repeating the updating for 53 sets of individually identified modal characteristics for different time records. A multi-objective optimization approach is used in the model updating of each set, considering a trade-off between the fit in the difference in natural frequencies between two states and the fit in the difference in eigenmode. It is concluded that the shell model provides the most accurate and reliable characterization of the evolution in damage from one state to another.
The work presented in the manuscript is valuable, in particular for which concerns the experimental data of the blade which are made publicly available on a repository of the institute of the first author. The damage identification presented in the manuscript is also of potential interest but I would like the authors to consider the following comments before it is given further consideration for publication: