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Smart Structures and Systems
  Volume 15, Number 1, January 2015, pages 151-167
DOI: http://dx.doi.org/10.12989/sss.2015.15.1.151
 


Instrumentation on structural health monitoring systems to real world structures
Jun Teng, Wei Lu, Runfa Wen and Ting Zhang

 
Abstract
    Instrumentation on structural health monitoring system imposes critical issues for applying the structural monitoring system to real world structures, for which not only on the configuration and geometry, but also aesthetics on the system to be monitored should be considered. To illustrate this point, two real world structural health monitoring systems, the structural health monitoring system of Shenzhen Vanke Center and the structural health monitoring system of Shenzhen Bay Stadium in China, are presented in the paper. The instrumentation on structural health monitoring systems of real world structures is addressed by providing the description of the structure, the purpose of the structural health monitoring system implementation, as well as details of the system integration including the installations on the sensors and acquisition equipment and so on. In addition, an intelligent algorithm on stress identification using measurements from multi-region is presented in the paper. The stress identification method is deployed using the fuzzy pattern recognition and Dempster-Shafer evidence theory, where the measurements of limited strain sensors arranged on structure are the input data of the method. As results, at the critical parts of the structure, the stress distribution evaluated from the measurements has shown close correlation to the numerical simulation results on the steel roof of the Beijing National Aquatics Center in China. The research work in this paper can provide a reference for the design and implementation of both real world structural health monitoring systems and intelligent algorithm to identify stress distribution effectively.
 
Key Words
    structural health monitoring; intelligent systems; information acquisition; stress distribution; fuzzy pattern recognition
 
Address
Jun Teng: School of Civil Engineering, Fujian University of technology, Fuzhou 350108,China;
Department of Civil and Environmental Engineering, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China
Wei Lu, Runfa Wen and Ting Zhang: Department of Civil and Environmental Engineering, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China
 

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