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Proceedings Paper

Decision uncertainty in a structural health monitoring system
Author(s): Martin DeSimio; Steven Olson; Mark Derriso
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Paper Abstract

This paper examines the effects of uncertainty in a structural health monitoring application. Decision uncertainty acknowledges that classification system decisions are probabilistic. The particular task of interest consists of detecting and localizing which one, if any, of fifteen fasteners is loose in a thermal protection system panel. From laboratory data collected during a three month interval, a benchmark classification system is designed to detect and localize loose fasteners and corresponding accuracies are computed. The performance of this system is measured in terms of probabilities of detection, localization, and false alarm. When the benchmark classifier is applied to an independent test set of over 4,900 trials, the probability of detection is 99.6%, the probability of localization is 98.0% and the probability of false alarm is 1.0%. A method is described for reducing the effects of uncertainty and applied to the benchmark classification system. With this processing, the probability of detection becomes 99.0%, the probability of localization becomes 97.6% and the probability of false alarm becomes 0.3%.

Paper Details

Date Published: 17 May 2005
PDF: 12 pages
Proc. SPIE 5764, Smart Structures and Materials 2005: Smart Structures and Integrated Systems, (17 May 2005); doi: 10.1117/12.599769
Show Author Affiliations
Martin DeSimio, iCAD, Inc. (United States)
Steven Olson, Univ. of Dayton Research Institute (United States)
Mark Derriso, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 5764:
Smart Structures and Materials 2005: Smart Structures and Integrated Systems
Alison B. Flatau, Editor(s)

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