Title

Damage Detection With Time Series Modeling Using Ambient Vibration Data: Experimental Verifications

Abstract

In this paper, structural condition assessment of a large scale 4-span bridge model using ambient vibration data is presented. An ARX model (Auto-Regressive models with eX-ogenous input) based damage detection methodology developed by the authors previously is used. Ambient vibration time histories are processed using Random Decrement (RD) to obtain pseudo-free response data. Then, ARX models are created for different sensor clusters by using the pseudo-free response of the structure. The output of each sensor in a cluster is used as an in-put to the ARX model to predict the output of the reference channel of that sensor cluster. After creating the ARX models for the healthy structure for each sensor cluster, these models are used for predicting the data from the damaged structure. The difference between the fit ratios is used as the Damage Feature (DF). Data from different damage cases are processed using the metho-dology and results are presented. It is shown that the methodology can successfully be used to detect and locate the applied damage in the structure.

Publication Date

1-1-2011

Publication Title

4th International Operational Modal Analysis Conference, IOMAC 2011

Number of Pages

169-176

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

84922641208 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84922641208

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