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      Implementation of a Probabilistic Structural Health Monitoring Method on a Highway Bridge

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      Advances in Civil Engineering
      Hindawi Limited

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          Abstract

          This paper describes the application of a probabilistic structural health monitoring (SHM) method to detect global damage in a highway bridge in Connecticut. The proposed method accounts for the variability associated with environmental and operational conditions. The bridge is a curved three-span steel dual-box girder bridge located in Hartford, Connecticut. The bridge, monitored since Fall 2001, experienced a period of settling in the Winter of 2002-2003. While this change was not associated with structural damage, it was observed in a permanent rotation of the bridge superstructure. Three damage measures are identified in this study: the value of fundamental natural frequency determined from peak picking of autospectral density functions of the bridge acceleration measurements; the magnitude of the peak acceleration measured during a truck crossing; the magnitude of the tilt measured at 10-minute intervals. These damage measures, including thermal effects, are shown to be random variables and associated Pvalues are calculated to determine if the current probability distributions are the same as the distributions of the baseline bridge data from 2001. Historical data measured during the settling of the bridge is used to verify the performance of the bridge, and the field implementation of the proposed method is described.

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          A Summary Review of Vibration-Based Damage Identification Methods

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            Detection of structural damage through changes in frequency: a review

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              Vibration-based structural damage identification

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                Author and article information

                Journal
                Advances in Civil Engineering
                Advances in Civil Engineering
                Hindawi Limited
                1687-8086
                1687-8094
                2012
                2012
                : 2012
                :
                : 1-9
                Article
                10.1155/2012/307515
                1ad30410-7c11-4096-9dc9-117f86e664ba
                © 2012

                http://creativecommons.org/licenses/by/3.0/

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