Smart Structures and Systems

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Damage detection on a full-scale highway sign structure with a distributed wireless sensor network

  • Sun, Zhuoxiong (School of Mechanical Engineering, Purdue University) ;
  • Krishnan, Sriram (School of Mechanical Engineering, Purdue University) ;
  • Hackmann, Greg (Department of Computer Science and Engineering, Washington University in St. Louis) ;
  • Yan, Guirong (Department of Civil Engineering, University of Texas at El Paso) ;
  • Dyke, Shirley J. (School of Mechanical Engineering, Purdue University) ;
  • Lu, Chenyang (Department of Computer Science and Engineering, Washington University in St. Louis) ;
  • Irfanoglu, Ayhan (School of Civil Engineering, Purdue University)
  • Received : 2014.01.27
  • Accepted : 2015.03.09
  • Published : 2015.07.25
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Abstract

Wireless sensor networks (WSNs) have emerged as a novel solution to many of the challenges of structural health monitoring (SHM) in civil engineering structures. While research projects using WSNs are ongoing worldwide, implementations of WSNs on full-scale structures are limited. In this study, a WSN is deployed on a full-scale 17.3m-long, 11-bay highway sign support structure to investigate the ability to use vibration response data to detect damage induced in the structure. A multi-level damage detection strategy is employed for this structure: the Angle-between-String-and-Horizon (ASH) flexibility-based algorithm as the Level I and the Axial Strain (AS) flexibility-based algorithm as the Level II. For the proposed multi-level damage detection strategy, a coarse resolution Level I damage detection will be conducted first to detect the damaged region(s). Subsequently, a fine resolution Level II damage detection will be conducted in the damaged region(s) to locate the damaged element(s). Several damage cases are created on the full-scale highway sign support structure to validate the multi-level detection strategy. The multi-level damage detection strategy is shown to be successful in detecting damage in the structure in these cases.

Keywords

Acknowledgement

Supported by : National Science Foundation

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