Journal
STRUCTURAL CONTROL & HEALTH MONITORING
Volume 29, Issue 2, Pages -Publisher
JOHN WILEY & SONS LTD
DOI: 10.1002/stc.2872
Keywords
damage identification; model updating; offshore wind turbine; operational modal analysis; structural health monitoring
Funding
- Louisiana Board of Regents [AWD-001515]
- Louisiana Transportation Research Center [20-3TIRE]
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This study proposes a two-step strategy for damage identification of offshore wind turbines via Finite Element (FE) model updating. The first step identifies the damaged component(s), while the second step focuses on exact damage localization and quantification. Results indicate that the proposed methodology can correctly identify most structural damage using operational data.
This study proposes a two-step strategy for damage identification of offshore wind turbines via Finite Element (FE) model updating. In this methodology, the first step identifies the damaged component(s) using a verified global mathematical model of the offshore wind turbine under operational wind and wave loading. Damaged components can be the tower, a certain blade, or the foundation. Natural frequencies and mode shapes obtained from operational modal analysis are used to formulate the objective function for deterministic model updating. With the identified damaged component(s) in the first step, the second step of the strategy focuses on exact damage localization and quantification of the damaged component(s). To this end, an FE model of a baseline 5 MW monopile offshore wind turbine is established using ANSYS. Wind and wave loading are applied to simulate the structural responses under different damage scenarios. In additional to natural frequencies and mode shapes, mode shape curvatures obtained in the second step are included in the objective function. Results indicate that the proposed methodology can correctly identify most structural damage on the offshore wind turbines using operational data. The proposed two-step damage identification strategy can circumvent the requirement of intensive computation due to full model updating of offshore wind turbine models and thus greatly improve the efficiency in real application.
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