Fault Detection of the Mooring system in Floating Offshore Wind Turbines based on the Wave-excited Linear Model

Journal Article (2020)
Author(s)

Yichao Liu (TU Delft - Mechanical Engineering)

Alessandro Fontanella (Politecnico di Milano)

Ping Wu (Zhejiang Sci-Tech University)

Riccardo M.G. Ferrari (TU Delft - Mechanical Engineering)

Jan Willem Van Wingerden (TU Delft - Mechanical Engineering)

Research Group
Team Jan-Willem van Wingerden
DOI related publication
https://doi.org/10.1088/1742-6596/1618/2/022049 Final published version
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Publication Year
2020
Language
English
Research Group
Team Jan-Willem van Wingerden
Journal title
Journal of Physics: Conference Series
Issue number
2
Volume number
1618
Article number
022049
Event
Science of Making Torque from Wind 2020, TORQUE 2020 (2020-09-28 - 2020-10-02), Online, Virtual, Online, Netherlands
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Abstract

Floating Offshore Wind Turbines (FOWTs) are more prone to suffer from faults and failures than bottom-fixed counterparts due to the severe wind and wave loads typical of deep water sites. In particular, mooring line faults may lead to unacceptably high operation and maintenance costs due to the limited accessibility of FOWTs. Detecting the mooring line faults is therefore critical, but the application of Fault Detection (FD) techniques has not been investigated yet. In this paper, an FD scheme based on a wave-excited linear model is developed to detect in a reliable way critical mooring line faults occurring at the fairlead and anchor ends. To reach the goal, a linear model of the FOWT is obtained by approximating the wave radiation and incident wave forces. Based on this model, an observer is built to predict the rigid rotor and platform dynamics. The FD scheme is thus implemented by comparing the Mahalanobis Distance of the observer prediction error against a probabilistic detection threshold. Numerical simulations in some selected fault scenarios show that the wave-excited linear model can predict the FOWT dynamics with good accuracy. Based on this, the FD scheme capabilities are demonstrated, showing that it is able to effectively detect two critical mooring line faults.