No abstract

The increasing number of installed wind turbines has led to a greater need for monitoring of their subcomponents. In particular, damages on rotor blades should be detected as early as possible, since they can cause long and hence expensive standstill times. In this work, a three-tier structural health monitoring framework is employed on the experimental data of a 34-m rotor blade for damage and ice detection. The structural health monitoring framework includes the functions of data normalization by clustering according to environmental and operational conditions, feature extraction, and hypothesis testing. In order to assess the framework and the methods applied with respect to ice detection, an ice accretion test was performed by gradually adding masses at the blade tip. First, a modal test by means of manual and impulse excitation was performed on the healthy blade and for all steps of the ice test. Subsequently, to induce damage, the blade was cyclically excited in edgewise direction for over 1 million cycles until failure occurred at the trailing edge. Finally, the initial modal test was repeated on the damaged blade. Modal parameters from system identification and further damage features, also called condition parameters, are presented and compared to each other. Results from the modal test show that structural changes due to damage at the trailing edge and added mass can be detected by changes in the condition parameters. Nevertheless, it is shown that some condition parameters exhibit higher sensitivity to damage than natural frequencies. Furthermore, a correlation between the amount of added mass and the changes in natural frequencies and some of the condition parameters is shown. For the analysis of the fatigue test, condition parameters were determined with and without prior data clustering according to the applied damage equivalent load, resulting in two realizations of the structural health monitoring framework. Results from the fatigue test show that the majority of condition parameters have good detection performance regarding structural change due to fatigue cracks and due to damage at the trailing edge for various confidence intervals. Finally, it is shown that the detection performance in the case of data clustering according to applied damage equivalent load is higher than without data clustering. This emphasizes the need of data normalization by clustering according to the environmental and operational conditions.

The bubble curtain is one of the most used measures to reduce underwater pile driving noise. A model of the local distribution of the effective wavenumber was developed. The bubble size distribution was derived from tank measurements. The local distribution of the air fraction was determined by means of an integral method. In a preliminary step, the transfer characteristics of a bubble curtain were studied. The results show a decrease of the transmission coefficient for higher frequencies and additionally for lower water depths. For lower frequencies, λ/2-transmission can be observed. Examining the noise mitigation of a bubble curtain under offshore conditions, a model of the acoustical scenario was developed. Two different offshore measurement sites are described in detail and compared to the modeling results. The distance between bubble curtain and the pile was identified as an important parameter affecting the noise mitigation. The presented approach shows an appropriate representation of the noise mitigation and allows, due to its generic definition, for future investigations of various aspects, e.g., the influence of the soil or the effect of an extra pile near system on the noise mitigation.

No abstract

Vibration-based Structural Health Monitoring is an ongoing field of research in many engineering disciplines. As for civil engineering, plenty of experimental structures have been erected in the past decades, both under laboratory and real-life conditions. Some of these facilities became a benchmark for different kinds of methods associated with Structural Health Monitoring such as damage analysis and Operational Modal Analysis, which led to fruitful developments in the global research community. When it comes to the continuous monitoring and assessment of the structural integrity of mechanical systems exposed to environmental and operational variability, the robustness and adaptability of the applied methods is of utmost importance. Such properties cannot be fully evaluated under laboratory conditions, which highlights the necessity of outdoor measurement campaigns. To this end, we introduce a test facility for Structural Health Monitoring comprising a lattice tower exposed to realistic conditions and featuring multiple reversible damage mechanisms. The structure located near Hanover in Northern Germany is densely equipped with sensors to capture the structural dynamics. The environmental conditions are monitored in parallel. The obtained continuous measurement data can be accessed online in an open repository. That is the foundation for benchmarks, consisting of a growing data set that enables the development, evaluation, and comparison of Structural Health Monitoring strategies and methods. In this article, we offer a documentation of the test facility and the data acquisition system. Lastly, we characterize the structural dynamics with the help of a finite element model and by analyzing several month of data.