TECHNICAL PAPERS
Mar 1, 2008

Energy Harvesting for Structural Health Monitoring Sensor Networks

Publication: Journal of Infrastructure Systems
Volume 14, Issue 1

Abstract

This paper reviews the development of energy harvesting for low-power embedded structural health monitoring (SHM) sensing systems. A statistical pattern recognition paradigm for SHM is first presented and the concept of energy harvesting for embedded sensing systems is addressed with respect to the data acquisition portion of this paradigm. Next, various existing and emerging sensing modalities used for SHM and their respective power requirements are summarized followed by a discussion of SHM sensor network paradigms, power requirements for these networks, and power optimization strategies. Various approaches to energy harvesting and energy storage are discussed and limitations associated with the current technology are addressed. The paper concludes by defining some future research directions that are aimed at transitioning the concept of energy harvesting for embedded SHM sensing systems from laboratory research to field-deployed engineering prototypes. Finally, it is noted that many of the technologies discussed herein are applicable to powering any type of low-power embedded sensing system regardless of the application.

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Go to Journal of Infrastructure Systems
Journal of Infrastructure Systems
Volume 14Issue 1March 2008
Pages: 64 - 79

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Received: Jan 4, 2007
Accepted: Jun 8, 2007
Published online: Mar 1, 2008
Published in print: Mar 2008

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Gyuhae Park
The Engineering Institute, Los Alamos National Laboratory, Los Alamos, NM 87545.
Tajana Rosing
Dept. of Computer Science and Engineering, Univ. of California, San Diego, La Jolla, CA 92093-0114.
Michael D. Todd
Dept. of Structural Engineering, Univ. of California, San Diego, La Jolla, CA 92093-0085.
Charles R. Farrar
The Engineering Institute, Los Alamos National Laboratory, Los Alamos, NM 87545.
William Hodgkiss
Dept. of Electrical and Computer Engineering, Univ. of California, San Diego, La Jolla, CA 92093-0701.

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