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Bayesian Analysis of the Phase II IASC–ASCE Structural Health Monitoring Experimental Benchmark Data

Ching, J. and Beck, J. L. (2004) Bayesian Analysis of the Phase II IASC–ASCE Structural Health Monitoring Experimental Benchmark Data. Journal of Engineering Mechanics, 130 (10). pp. 1233-1244. ISSN 0733-9399. http://resolver.caltech.edu/CaltechAUTHORS:20120810-112646766

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Abstract

A two-step probabilistic structural health monitoring approach is used to analyze the Phase II experimental benchmark studies sponsored by the IASC–ASCE Task Group on Structural Health Monitoring. This study involves damage detection and assessment of the test structure using experimental data generated by hammer impact and ambient vibrations. The two-step approach involves modal identification followed by damage assessment using the pre- and post-damage modal parameters based on the Bayesian updating methodology. An Expectation–Maximization algorithm is proposed to find the most probable values of the parameters. It is shown that the brace damage can be successfully detected and assessed from either the hammer or ambient vibration data. The connection damage is much more difficult to reliably detect and assess because the identified modal parameters are less sensitive to connection damage, allowing the modeling errors to have more influence on the results.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://ascelibrary.org/doi/abs/10.1061/%28ASCE%290733-9399%282004%29130%3A10%281233%29PublisherArticle
http://dx.doi.org/10.1061/(ASCE)0733-9399(2004)130:10(1233) DOIArticle
Additional Information:© ASCE / OCTOBER 2004. The manuscript for this paper was submitted for review and possible publication on July 28, 2003; approved on November 14, 2003.
Subject Keywords:Damage assessment; Bayesian analysis; Identification; Bench marks; Structural analysis; Modal analysis
Record Number:CaltechAUTHORS:20120810-112646766
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20120810-112646766
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:33088
Collection:CaltechAUTHORS
Deposited By: Sydney Garstang
Deposited On:13 Aug 2012 17:33
Last Modified:24 Feb 2014 19:05

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