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Proceedings Paper

Embedded transmissibility function analysis for damage detection in a mobile sensor network
Author(s): Xiaohua Yi; Dapeng Zhu; Yang Wang; Jiajie Guo; Kok-Meng Lee
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Paper Abstract

Structural health monitoring (SHM) and damage detection have attracted great interest in recent decades, in meeting the challenges of assessing the safety condition of large-scale civil structures. By wiring remote sensors directly to a centralized data acquisition system, traditional structural health monitoring systems are usually costly and the installation is time-consuming. Recent advances in wireless sensing technology have made it feasible for structural health monitoring; furthermore, the computational core in a wireless sensing unit offers onboard data interrogation. In addition to wireless sensing, the authors have recently developed a mobile sensing system for providing high spatial resolution and flexible sensor deployment in structural health monitoring. In this study, transmissibility function analysis is embedded in the mobile sensing node to perform onboard and in-network structural damage detection. The system implementation is validated using a laboratory 2D steel portal frame. Simulated damage is applied to the frame structure, and the damage is successfully identified by two mobile sensing nodes that autonomously navigate through the structure.

Paper Details

Date Published: 1 April 2010
PDF: 9 pages
Proc. SPIE 7647, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2010, 764729 (1 April 2010); doi: 10.1117/12.847256
Show Author Affiliations
Xiaohua Yi, Georgia Institute of Technology (United States)
Dapeng Zhu, Georgia Institute of Technology (United States)
Yang Wang, Georgia Institute of Technology (United States)
Jiajie Guo, Georgia Institute of Technology (United States)
Kok-Meng Lee, Georgia Institute of Technology (United States)


Published in SPIE Proceedings Vol. 7647:
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2010
Masayoshi Tomizuka, Editor(s)

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