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Damage Identification of A TLP Floating Wind Turbine by Meta-Heuristic Algorithms

机译:荟萃启发式算法TLP浮动风力涡轮机的损伤识别

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摘要

Damage identification of the offshore floating wind turbine by vibration/dynamic signals is one of the important and new research fields in the Structural Health Monitoring(SHM). In this paper a new damage identification method is proposed based on meta-heuristic algorithms using the dynamic response of the TLP(Tension-Leg Platform) floating wind turbine structure. The Genetic Algorithms(GA), Artificial Immune System(AIS), Particle Swarm Optimization(PSO), and Artificial Bee Colony(ABC) are chosen for minimizing the object function, defined properly for damage identification purpose. In addition to studying the capability of mentioned algorithms in correctly identifying the damage, the effect of the response type on the results of identification is studied. Also, the results of proposed damage identification are investigated with considering possible uncertainties of the structure. Finally, for evaluating the proposed method in real condition, a 1/100 scaled experimental setup of TLP Floating Wind Turbine(TLPFWT) is provided in a laboratory scale and the proposed damage identification method is applied to the scaled turbine.

著录项

  • 来源
    《中国海洋工程(英文版)》 |2015年第6期|891-902|共12页
  • 作者

    M.M.Ettefagh;

  • 作者单位

    Mechanical Engineering Department University of Tabriz Tabriz Iran;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-19 04:48:07
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