Multi-objective optimization strategies for damage detection using cloud model theory

Zhou Jin, Akira Mita, Li Rongshuai

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Cloud model is a new mathematical representation of linguistic concepts, which shows potentials for uncertainty mediating between the concept of a fuzzy set and that of a probability distribution. This paper utilizes cloud model theory as an uncertainty analyzing tool for noise-polluted signals, which formulates membership degree functions of residual errors that quantify the difference between the prediction from simulated model and the actual measured time history at each time interval. With membership degree functions a multi-objective optimization strategy is proposed, which minimizes multiple error terms simultaneously. Its non-domination-based convergence provides a stronger constraint that enables robust identification of damages with lower damage negative false. Simulation results of a structural system under noise polluted signals are presented to demonstrate the effectiveness of the proposed method.

本文言語English
ホスト出版物のタイトルHealth Monitoring of Structural and Biological Systems 2012
DOI
出版ステータスPublished - 2012 6 6
イベントHealth Monitoring of Structural and Biological Systems 2012 - San Diego, CA, United States
継続期間: 2012 3 122012 3 15

出版物シリーズ

名前Proceedings of SPIE - The International Society for Optical Engineering
8348
ISSN(印刷版)0277-786X

Other

OtherHealth Monitoring of Structural and Biological Systems 2012
国/地域United States
CitySan Diego, CA
Period12/3/1212/3/15

ASJC Scopus subject areas

  • 電子材料、光学材料、および磁性材料
  • 凝縮系物理学
  • コンピュータ サイエンスの応用
  • 応用数学
  • 電子工学および電気工学

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