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A Bayesian Probabilistic Approach to Damage Detection for Civil Structures

Sohn, H (Author)
Law, KH (Author)
Date created:
Type of resource:
Technical report
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.
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
John A. Blume Earthquake Engineering Center Technical Report Series
Related item:
John A. Blume Earthquake Engineering Center
damage detection
probabilistic seismic hazard analysis
computer modeling
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