Smart Structures and Systems

  • 제13권3호
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  • Pages.389-406
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  • 2014
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Optimal sensor placement for mode shapes using improved simulated annealing

  • Tong, K.H. (Faculty of Civil Engineering, Universiti Teknologi) ;
  • Bakhary, Norhisham (Faculty of Civil Engineering, Universiti Teknologi) ;
  • Kueh, A.B.H. (Construction Research Centre, Universiti Teknologi) ;
  • Yassin, A.Y. Mohd (Faculty of Civil Engineering, Universiti Teknologi)
  • 투고 : 2012.10.30
  • 심사 : 2013.04.02
  • 발행 : 2014.03.25
⟨ 이전 논문 다음 논문 ⟩

초록

Optimal sensor placement techniques play a significant role in enhancing the quality of modal data during the vibration based health monitoring of civil structures, where many degrees of freedom are available despite a limited number of sensors. The literature has shown a shift in the trends for solving such problems, from expansion or elimination approach to the employment of heuristic algorithms. Although these heuristic algorithms are capable of providing a global optimal solution, their greatest drawback is the requirement of high computational effort. Because a highly efficient optimisation method is crucial for better accuracy and wider use, this paper presents an improved simulated annealing (SA) algorithm to solve the sensor placement problem. The algorithm is developed based on the sensor locations' coordinate system to allow for the searching in additional dimensions and to increase SA's random search performance while minimising the computation efforts. The proposed method is tested on a numerical slab model that consists of two hundred sensor location candidates using three types of objective functions; the determinant of the Fisher information matrix (FIM), modal assurance criterion (MAC), and mean square error (MSE) of mode shapes. Detailed study on the effects of the sensor numbers and cooling factors on the performance of the algorithm are also investigated. The results indicate that the proposed method outperforms conventional SA and Genetic Algorithm (GA) in the search for optimal sensor placement.

키워드

참고문헌

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