Synergy of random balance design method and intelligent optimization technique for model updating of the 4MW offshore wind turbine benchmark

Xu, Kai, Meng, Ankang, Chang, Shuang, Liu, Dianzi and Liu, Fushun (2024) Synergy of random balance design method and intelligent optimization technique for model updating of the 4MW offshore wind turbine benchmark. Marine Structures, 93. ISSN 0951-8339

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Abstract

The technical challenges for model updating of real marine engineering structures include the extraction of modal parameters associated with incomplete measurement information and the correction of a large number of structural parameters. As it is difficult to verify the effectiveness of model updating methods for engineering applications, the representative models have to be adopted in finite element (FE) analysis or lab-scale tests, leading to the incomplete reflection of actual structural performances. Based on these factors, a practical model updating method is developed in this study to make full use of field measurement data from a 4MW offshore wind turbine for the accurate estimation of structural parameters using the random balance designs-Fourier amplitude sensitivity test (RBD-FAST) strategy and an improved particle swarm optimization (IPSO). Leveraging the measured acceleration signals from offshore wind turbines under the conditions including operation, shutdown, collision and typhoon scenarios, the complex exponential decomposition method is applied to accurately extract the time-varying acceleration components (TVAC) for the construction of the frequency response function (FRF). Following that, RBD-FAST is implemented into IPSO with adaptive inertia weights and asynchronously varying learning factors to enable efficient selection of numerous updated physical parameters, thus improving time cost and computational accuracy. The correctness of the proposed method is verified by a numerical jacket platform model. Furthermore, the 4MW offshore wind turbine benchmark is developed to assess the feasibility of the proposed model updating method using field measured data from different scenarios. Results show that the synergy of RBD-FAST and IPSO in the proposed method can accurately update parameters and minimize a maximum discrepancy of 0.8970% for the first-three orders of natural frequencies between the benchmark and the updated models in the collision scenario. Summarily, the present work provides a potential technique and practical engineering references for model updating of offshore wind turbines subject to harsh marine environments.

Item Type:	Article
Additional Information:	Funding Information: The authors acknowledge the financial support of the National Outstanding Youth Science Fund Project of National Natural Science Foundation of China (52125106), the National Natural Science Foundation project, China (U22A20243) and the National Natural Science Foundation project, China (52001291).
Uncontrolled Keywords:	field measured data,improved particle swarm optimization,model updating,offshore wind turbine,random balance design,materials science(all),ocean engineering,mechanics of materials,mechanical engineering ,/dk/atira/pure/subjectarea/asjc/2500
Faculty \ School:	Faculty of Science > School of Engineering
Related URLs:	http://www.scopus.com/inward/record.url?...
Depositing User:	LivePure Connector
Date Deposited:	21 Oct 2023 01:02
Last Modified:	07 Nov 2023 02:49
URI:	https://ueaeprints.uea.ac.uk/id/eprint/93385
DOI:	10.1016/j.marstruc.2023.103533

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