Experimental investigation on multi-objective multi-type sensor optimal placement for structural damage detection

Jian Fu Lin, You Lin Xu, Sheng Zhan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

11 Citations (Scopus)

Abstract

An optimal sensor placement with multiple types of sensors could provide informative data of a structure to facilitate its structural damage detection. A response covariance-based multi-objective multi-type sensor optimal placement method has been thus developed. To validate this method, an experimental investigation was designed and performed in terms of a nine-bay three-dimensional frame structure, and the experimental details and results are presented in this article. The frame structure was first built, and a finite element model of the frame structure was constructed and updated. The proposed method was then applied to the finite element model to find the optimal sensor placement configuration. The multi-type sensors were then installed on the frame structure according to the determined optimal sensor numbers and positions. Different damage scenarios were then generated on the frame structure. These damage scenarios covered single and multiple damage cases occurring at different locations with different damage severities. A series of experiments, including the optimal and non-optimal sensor placements, were finally carried out, and the measurement data were used together with the finite element model to identify damage quantitatively. The identification results show that the optimal multi-type sensor placement determined by the proposed method could provide accurate damage localization and satisfactory damage quantitation and that the optimal sensor placement yielded better damage identification than the non-optimal sensor placement.

Original languageEnglish
Pages (from-to)882-901
Number of pages20
JournalStructural Health Monitoring
Volume18
Issue number3
DOIs
Publication statusPublished - 1 May 2019

Keywords

  • damage detection
  • multi-objective optimization
  • Multi-type sensor placement
  • Pareto-optimal solution
  • response covariance sensitivity
  • response independence

ASJC Scopus subject areas

  • Biophysics
  • Mechanical Engineering

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