Distributed sensing for high-quality structural health monitoring using WSNs

Xuefeng Liu, Jiannong Cao, Wen Zhan Song, Peng Guo, Zongjian He

Research output: Journal article publicationJournal articleAcademic researchpeer-review

41 Citations (Scopus)


Due to the low cost and ease of deployment, wireless sensor networks (WSNs) are emerging as sensing paradigms that the structural engineering field has begun to consider as substitutes for traditional tethered structural health monitoring (SHM) systems. Different from other applications of WSNs such as environmental monitoring, SHM applications are much more data intensive and it is not feasible to stream the raw data back to the server due to the severe bandwidth and energy limitations of low-power sensor networks. In-network processing is a promising approach to address this problem but designing distributed versions for the sophisticated SHM algorithms is much more challenging because SHM algorithms are computationally intensive, and involve data-level collaboration of multiple sensors. In this paper, we select a classical SHM algorithm: the eigen-system realization algorithm (ERA), and propose a few distributed ERAs suitable for WSNs. In particular, we first design a method to incrementally calculate the ERA and then propose three schemes upon which the incremental ERA can be carried out along an Hamiltonian path, along a path in the minimum connected dominating set (MCDS) and along the shortest path tree (SPT). The efficacy of these schemes are demonstrated and compared through both simulation experiment. We believe the proposed schemes can also serve as a guideline when applying WSNs for other applications like SHM which are also data-intensive and involve sophisticated signal processing of collected information.
Original languageEnglish
Article number6776483
Pages (from-to)738-747
Number of pages10
JournalIEEE Transactions on Parallel and Distributed Systems
Issue number3
Publication statusPublished - 1 Mar 2015


  • distributed algorithms
  • structural health monitoring
  • Wireless sensor networks

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics


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