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Proceedings Paper

Neural network damage detection in a bridge element
Author(s): William B. Spillman; Dryver R. Huston; Peter L. Fuhr; Jeffrey R. Lord
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Paper Abstract

Smart structures technology is being increasingly applied to civil structure applications. In particular, development of health monitoring for bridge structures is of considerable importance. In order to explore the possibility of developing such a system, an investigation was carried out on a scale model steel bridge element using an attached sensor system consisting of two point sensors (piezoelectric accelerometers) and one integrating sensor (fiber optic modal sensor). The model element was selectively configured to produce the equivalent of a number of damage conditions. For each condition, it was physically perturbed. The sensor outputs were then used as inputs to a neural net which then provided an estimate of structural damage. A reasonable correlation between net output and actual damage indicated that this type of health monitoring system offers potential for practical application on full scale bridge structures.

Paper Details

Date Published: 12 July 1993
PDF: 12 pages
Proc. SPIE 1918, Smart Structures and Materials 1993: Smart Sensing, Processing, and Instrumentation, (12 July 1993); doi: 10.1117/12.147985
Show Author Affiliations
William B. Spillman, Univ. of Vermont (United States)
Dryver R. Huston, Univ. of Vermont (United States)
Peter L. Fuhr, Univ. of Vermont (United States)
Jeffrey R. Lord, Univ. of Vermont (United States)


Published in SPIE Proceedings Vol. 1918:
Smart Structures and Materials 1993: Smart Sensing, Processing, and Instrumentation
Richard O. Claus, Editor(s)

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