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Decentralized system identification using stochastic subspace identification for wireless sensor networks.

Soojin Cho1, Jong-Woong Park2, Sung-Han Sim3

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Wireless sensor networks (WSNs) offer an economical solution for structural monitoring. This study proposes a decentralized system identification method for WSNs, validated on a 5-story building model.

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Area of Science:

  • Civil Engineering
  • Structural Health Monitoring
  • Wireless Sensor Networks

Background:

  • Conventional wired structural monitoring systems are expensive to install and maintain.
  • Wireless sensor networks (WSNs) provide a feasible and economical alternative for dense sensor deployment on large structures.
  • WSNs necessitate decentralized computing due to wireless communication limitations.

Purpose of the Study:

  • To propose a decentralized system identification method for WSNs.
  • To implement Stochastic Subspace Identification (SSI)-based Decentralized System Identification (SDSI) within a WSN framework.
  • To experimentally validate the performance of SDSI in a laboratory setting.

Main Methods:

  • Utilizing Stochastic Subspace Identification (SSI) for system identification.
  • Implementing SSI-based Decentralized System Identification (SDSI) on Imote2 wireless sensors.
  • Deploying sensors in a hierarchical WSN architecture with tight scheduling.
  • Conducting laboratory tests on a 5-story shear building model.

Main Results:

  • Successful experimental verification of the proposed SDSI method.
  • Demonstrated feasibility of decentralized system identification in WSNs for structural monitoring.
  • Validated the performance of SDSI on a multi-story building model.

Conclusions:

  • SDSI is a viable approach for decentralized system identification in WSNs.
  • The proposed method overcomes limitations of centralized processing in WSNs.
  • This technology enables cost-effective and efficient structural health monitoring.