Abstract
Cost-competitiveness of offshore wind depends heavily in its capacity to switch preventive maintenance to condition-based maintenance. That is, to monitor the actual condition of the wind turbine (WT) to decide when and which maintenance needs to be done. In particular, structural health monitoring (SHM) to monitor the foundation (support structure) condition is of utmost importance in offshore-fixed wind turbines. In this work a SHM strategy is presented to monitor online and during service a WT offshore jacket-type foundation. Standard SHM techniques, as guided waves with a known input excitation, cannot be used in a straightforward way in this particular application where unknown external perturbations as wind and waves are always present. To face this challenge, a vibration-response-only SHM strategy is proposed via machine learning methods. In this sense, the fractal dimension is proposed as a suitable feature to identify and classify different types of damage. The proposed proof-of-concept technique is validated in an experimental laboratory down-scaled jacket WT foundation undergoing different types of damage.
Highlights
Structural health monitoring’s (SHM) main purpose is to diagnose in time damage that affects the integrity of a structure and determine whether repair or reinforcement actions are required to avoid or delay its degradation
As it has been detailed in Sections 3.3.1–3.3.2, the classification models used in this work are k nearest neighbors (kNN), quadratic support vector machines (SVM) and Gaussian
The results of the present approach using the fractal dimension to build the feature vector and kNN, quadratic SVM and Gaussian SVM are presented in Sections 4.2–4.4, respectively
Summary
Structural health monitoring’s (SHM) main purpose is to diagnose in time damage that affects the integrity of a structure and determine whether repair or reinforcement actions are required to avoid or delay its degradation. SHM strategies consist of the following steps:. It is important to note that, in a wide variety of applications, guided waves, which is a nondestructive approach, is the usual standard. This approach relies on exciting the structure with low frequency ultrasonic waves and sensing the reflected response waves. The method relies heavily on the fact that the input excitation is known and that other perturbations can be filtered or neglected. In civil infrastructures, such as bridges, it is feasible to assume that external perturbations can be neglected or filtered with respect to the induced excitation, see [1,2]
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