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Optimal sensor placement for modal identification of structures using genetic algorithms—a case study: the olympic stadium in Cali, Colombia

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  • A. Cruz
  • W. Vélez
  • P. Thomson

Abstract

Adequate sensor placement plays a key role in such fields as system identification, structural control, damage detection and structural health monitoring of flexible structures. In recent years, interest has increased in the development of methods for determining an arrangement of sensors suitable for characterizing the dynamic behavior of a given structure. This paper describes the implementation of genetic algorithms as a strategy for optimal placement of a predefined number of sensors. The method is based on the maximization of a fitness function that evaluates sensor positions in terms of natural frequency identification effectiveness and mode shape independence under various occupation and excitation scenarios using a custom genetic algorithm. A finite element model of the stadium was used to evaluate modal parameters used in the fitness function, and to simulate different occupation and excitation scenarios. The results obtained with the genetic algorithm strategy are compared with those obtained from applying the Effective Independence and Modal Kinetic Energy sensor placement techniques. The sensor distribution obtained from the proposed strategy will be used in a structural health monitoring system to be installed in the stadium. Copyright Springer Science+Business Media, LLC 2010

Suggested Citation

  • A. Cruz & W. Vélez & P. Thomson, 2010. "Optimal sensor placement for modal identification of structures using genetic algorithms—a case study: the olympic stadium in Cali, Colombia," Annals of Operations Research, Springer, vol. 181(1), pages 769-781, December.
  • Handle: RePEc:spr:annopr:v:181:y:2010:i:1:p:769-781:10.1007/s10479-009-0576-6
    DOI: 10.1007/s10479-009-0576-6
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    Cited by:

    1. Miroslav Marić & Zorica Stanimirović & Srdjan Božović, 2015. "Hybrid metaheuristic method for determining locations for long-term health care facilities," Annals of Operations Research, Springer, vol. 227(1), pages 3-23, April.

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