Damage detection of TLP and Spar floating wind turbine using dynamic response of the structure. (1st October 2016)

• Record Type: Journal Article
• Authors: Jamalkia, Aysan; Ettefagh, Mir Mohammad; Mojtahedi, Alireza
• Is Part Of: Ocean engineering. Volume 125(2016)
• Page Start: 191
• Page End: 202
• Publication Date: 2016-10-01
• Subjects: SHM Structural health monitoring -- FWT floating wind turbine -- TLP tension leg platform -- FLS Fuzzy logic system -- MCS Monte Carlo Simulation -- FC fuzzy classification -- SR success rate -- EOMs equations of motion -- TPA tower-platform-assembly -- RNA rotor-nacelle-assembly -- DOFs degrees of freedom -- CM center-mass -- MWL Mean Water Level; Damage detection -- Floating wind turbine -- Fuzzy logic -- Multi body dynamics; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2016.08.009
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: Structural health monitoring (SHM) is essential for ensuring the structural safety performance during the service life. The process is of paramount importance in the case of the floating wind turbine (FWT) due to the structural parts, subjected to the marine environmental risky conditions. In this paper a fuzzy-based damage detection method, using dynamic response of the FWT structure, is proposed. In the first step, the nonlinear motion equations of the FWT system are derived using the theorem of angular momentum and Newton's second law. Then the variation values of the mean amplitude of dynamic response and frequency characteristics of the structure due to stiffness changes of mooring lines (simulated damage) are considered as input features to the fuzzy system. Also the fuzzy system is trained based on calibrating of the membership functions by defining the damage classes properly. The proposed method is applied on two types of the FWT, Tension Leg Platform (TLP) and Spar. The simulation results show that the proposed method is able to identify the damage classes with acceptable success rate (SR). Highlights: Fully coupled dynamic equations of healthy and damaged floating wind turbine are extracted and simulated using Euler-Newton and Runge-Kutta Method. Damages are simulated due to stiffness changes of mooring lines. Damage effects on dynamic response of TLP and Spar floating wind turbine are studied. A damage diagnosis method, based on fuzzy logic system, is proposed. The mean amplitude of dynamic response and dominant frequency of the turbine structure are considered as input features to the fuzzy system.