Title

Damage Assessment Using A Novel Modified Time Series Analysis Methodology

Abstract

Data analysis for large amounts of data efficiently and effectively has been a critical issue for structural health monitoring of civil infrastructure systems. In this study, a novel approach using a modified time series analysis methodology is used to detect, locate, and quantify structural changes. In this methodology, ARX models (Auto-Regressive models with exogenous input) are created for different sensor clusters by using the free response of the structure. The output of each sensor in a cluster is used as an input to the ARX model to predict the output of the reference channel of that sensor cluster. After the ARX models for the healthy structure at each DOF are created, the same models are used for predicting the data from the damaged structure. The difference between the fit ratios is used as damage indicating feature. The methodology is applied to numerical and experimental data coming from a steel grid structure and it is shown that the approach is successfully used for identification, localization, and quantification of different damage cases. The potential and advantages of the methodology are discussed along with the analysis results. The limitations and shortcomings of the methodology are also addressed.

Publication Date

1-1-2009

Publication Title

Structural Health Monitoring 2009: From System Integration to Autonomous Systems - Proceedings of the 7th International Workshop on Structural Health Monitoring, IWSHM 2009

Volume

1

Number of Pages

462-470

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

79955745204 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/79955745204

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