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Proceedings Paper

Bayesian probabilistic modeling for damage assessment in a bolted frame
Author(s): Colin Haynes; Michael Todd
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Paper Abstract

This paper presents the development of a Bayesian framework for optimizing the design of a structural health monitoring (SHM) system. Statistical damage detection techniques are applied to a geometrically-complex, three-story structure with bolted joints. A sparse network of PZT sensor-actuators is bonded to the structure, using ultrasonic guided waves in both pulse-echo and pitch-catch modes to inspect the structure. Receiver operating characteristics are used to quantify the performance of multiple features (or detectors). The detection rate of the system is compared across different types and levels of damage. A Bayesian cost model is implemented to determine the best performing network.

Paper Details

Date Published: 18 April 2012
PDF: 9 pages
Proc. SPIE 8348, Health Monitoring of Structural and Biological Systems 2012, 83480D (18 April 2012); doi: 10.1117/12.914635
Show Author Affiliations
Colin Haynes, Univ. of California, San Diego (United States)
Michael Todd, Univ. of California, San Diego (United States)

Published in SPIE Proceedings Vol. 8348:
Health Monitoring of Structural and Biological Systems 2012
Tribikram Kundu, Editor(s)

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