Abstract
For application in operational modal analysis considering simultaneously the temporal and spatial response data of multi-channel measurements, the multivariate-autoregressive (MV-AR) model was used. The parameters of MV-AR model are estimated by using the least squares method via the implementation of the QR factorization as an essential numerical tool and are used to extract the structural damage sensitive features. These parameters are used to develop the Vectors of autoregressive model and Mahalanobis distance, and then to identify the damage features and damage locations. Verification of the proposed method using a series of white noise response data of a steel structure is demonstrated. This method is thus very effective for damage detection in case of ambient vibrations dealing with output-only modal analysis. In addition, comparisons and discussions on the proposed method with other methods, such as stochastic subspace identification and wavelet-based energy index, are also presented.
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Acknowledgements
The authors wish to express their thanks to National Center for Research on Earthquake Engineering, NARL, for developing the two test specimens and conduct the shaking table tests. The support from Ministry of Science & Technology (Taiwan) under grant No. MOST 103-2625-M-002-006 is acknowledged.
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© 2016 The Society for Experimental Mechanics, Inc.
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Loh, CH., Chan, CK. (2016). Damage Assessment of Steel Structures Using Multi-Autoregressive Model. In: Pakzad, S., Juan, C. (eds) Dynamics of Civil Structures, Volume 2. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-29751-4_1
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DOI: https://doi.org/10.1007/978-3-319-29751-4_1
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