Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

Jian Fu Lin, You Lin Xu, Siu Seong Law

Research output: Journal article publicationJournal articleAcademic researchpeer-review

44 Citations (Scopus)


A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

Original languageEnglish
Pages (from-to)568-589
Number of pages22
JournalJournal of Sound and Vibration
Publication statusPublished - 26 May 2018


  • Damage detection
  • Multi-objective optimization
  • Multi-type sensor placement
  • Pareto-optimal solution
  • Response covariance sensitivity
  • Response independence

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Mechanics of Materials
  • Acoustics and Ultrasonics
  • Mechanical Engineering


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