A Bayesian Probabilistic Approach to Damage Detection for Civil Structures
Abstract/Contents
- Abstract
There have been increased economic and societal demands to periodically monitor the safety of structures against long-term deterioration, and to ensure their safety and adequate performance during the life span of the structures.
In this work, a Bayesian probabilistic framework for damage detection is proposed for the continuous monitoring of structures. The idea is to search for the most probable damage event by comparing the relative probabilities for different damage scenarios. The formulation of the relative posterior probability is based on an output error, which is defined as the difference between the estimated vibration parameters and the theoretical ones from the analytical model. The Bayesian approach is shown (1) to take into account the uncertainties in the measurement and the analytical modeling, (2) to perform damage diagnosis with a relatively small number of measurement points and a few modes, and (3) to systematically extract information from continuously obtained test data. A branch-and-bound search scheme is devised to expedite the search for the most likely damage event without exhaustively examining all possible damage cases.
As an alternative to modal vectors, load-dependent Ritz vectors are incorporated into the Bayesian framework. The following advantages of Ritz vectors over modal vectors are shown: (1) in general, load-dependent Ritz vectors are more sensitive to damage than the corresponding modal vectors, and (2) by a careful selection of load patterns, substructures of interest can be made more observable. Furthermore, a procedure to extract Ritz vectors from vibration test is proposed, and the procedure is successfully demonstrated using experimental test data.
Data from vibration tests of civil structures indicate that the environmental effects such as temperature, traffic loading, humidity can often mask subtle structural changes caused by damage. A linear adaptive filter is presented to discriminate the changes of modal parameters due to temperature changes from those caused by structural damage or other environmental effects. Results based on the field vibration test of a bridge indicate that the filter can reproduce the temporal variability of the frequencies so that the thermal effects on the vibration parameters can be differentiated from other environmental effects or potential structural damage.
Description
Type of resource | text |
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Date created | January 1999 |
Language | English |
Creators/Contributors
Author | Sohn, H | |
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Author | Law, KH |
Subjects
Subject | damage detection |
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Subject | probabilistic seismic hazard analysis |
Subject | computer modeling |
Genre | Technical report |
Bibliographic information
Related item | |
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Location | https://purl.stanford.edu/bq540dj5997 |
Access conditions
- Use and reproduction
- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
- License
- This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).
Preferred citation
- Preferred Citation
- Sohn, H and Law, KH. (1999). A Bayesian Probabilistic Approach to Damage Detection for Civil Structures. John A Blume Earthquake Engineering Center Technical Report 131. Stanford Digital Repository. Available at: http://purl.stanford.edu/bq540dj5997
Collection
John A. Blume Earthquake Engineering Center Technical Report Series
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- Contact
- jabeec-email@stanford.edu
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