Flexible smart sensor framework for autonomous structural health monitoring

  • Rice, Jennifer A. (Department of Civil and Environmental Engineering, Texas Tech University) ;
  • Mechitov, Kirill (Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign) ;
  • Sim, Sung-Han (Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign) ;
  • Nagayama, Tomonori (Department of Civil Engineering, University of Tokyo) ;
  • Jang, Shinae (Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign) ;
  • Kim, Robin (Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign) ;
  • Spencer, Billie F. Jr. (Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign) ;
  • Agha, Gul (Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign) ;
  • Fujino, Yozo (Department of Civil Engineering, University of Tokyo)
  • Received : 2009.11.13
  • Accepted : 2010.02.18
  • Published : 2010.07.25


Wireless smart sensors enable new approaches to improve structural health monitoring (SHM) practices through the use of distributed data processing. Such an approach is scalable to the large number of sensor nodes required for high-fidelity modal analysis and damage detection. While much of the technology associated with smart sensors has been available for nearly a decade, there have been limited numbers of fulls-cale implementations due to the lack of critical hardware and software elements. This research develops a flexible wireless smart sensor framework for full-scale, autonomous SHM that integrates the necessary software and hardware while addressing key implementation requirements. The Imote2 smart sensor platform is employed, providing the computation and communication resources that support demanding sensor network applications such as SHM of civil infrastructure. A multi-metric Imote2 sensor board with onboard signal processing specifically designed for SHM applications has been designed and validated. The framework software is based on a service-oriented architecture that is modular, reusable and extensible, thus allowing engineers to more readily realize the potential of smart sensor technology. Flexible network management software combines a sleep/wake cycle for enhanced power efficiency with threshold detection for triggering network wide operations such as synchronized sensing or decentralized modal analysis. The framework developed in this research has been validated on a full-scale a cable-stayed bridge in South Korea.


Supported by : National Science Foundation


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