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A fixed-order time series model for damage detection and localization

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Abstract

Time series modeling has great potential as a tool for damage detection. However, there are still a number of issues that need to be addressed before it can be effectively used for damage detection in the context of structural health monitoring (SHM). This paper presents a novel time series method directly derived from equation of motion (EOM) for damage detection. One of the unique advantages of the proposed method is that the order of the time series model is determined from the EOM, and thus, it is fixed, which could facilitate an easier automation and improve the computational efficiency. For the proposed method, fixed-order time series models are created for different sensor clusters using the output only vibration data from baseline and unknown states of the structure. Then, two different damage features (DFs) are developed from these models to identify the existence and location of the damage. To verify this method, an experimental steel grid structure with different damage cases applied is utilized. Two different DFs using fit ratios and coefficients are used to detect damage, and the results are compared. It is shown that the proposed method could identify the existence and location of damage and assess the relative severity successfully in most cases using either fit ratios or coefficients as DFs.

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Acknowledgments

This research was supported by the Natural Sciences and Engineering Research Council of Canada through the Discovery Grants.

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Authors and Affiliations

  1. Department of Civil and Environmental Engineering, University of Alberta, Edmonton, AB, T6G 2W2, Canada

    Qipei Mei & Mustafa Gül

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  1. Qipei Mei
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  2. Mustafa Gül
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Correspondence to Mustafa Gül.

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Mei, Q., Gül, M. A fixed-order time series model for damage detection and localization. J Civil Struct Health Monit 6, 763–777 (2016). https://doi.org/10.1007/s13349-016-0196-1

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  • DOI: https://doi.org/10.1007/s13349-016-0196-1

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