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    Sparse and low-rank methods in structural system identification and monitoring

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    Author
    Nagarajaiah, Satish
    Date
    2017
    Abstract
    This paper presents sparse and low-rank methods for explicit modeling and harnessing the data structure to address the inverse problems in structural dynamics, identification, and data-driven health monitoring. In particular, it is shown that the structural dynamic features and damage information, intrinsic within the structural vibration response measurement data, possesses sparse and low-rank structure, which can be effectively modeled and processed by emerging mathematical tools such as sparse representation (SR), and low-rank matrix decomposition. It is also discussed that explicitly modeling and harnessing the sparse and low-rank data structure could benefit future work in developing data-driven approaches towards rapid, unsupervised, and effective system identification, damage detection, as well as massive SHM data sensing and management.
    Citation
    Nagarajaiah, Satish. "Sparse and low-rank methods in structural system identification and monitoring." Procedia Engineering, 199, (2017) Elsevier: 62-69. https://doi.org/10.1016/j.proeng.2017.09.153.
    Published Version
    https://doi.org/10.1016/j.proeng.2017.09.153
    Type
    Journal article
    Publisher
    Elsevier
    Citable link to this page
    https://hdl.handle.net/1911/97802
    Rights
    This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives license
    Link to License
    https://creativecommons.org/licenses/by-nc-nd/4.0/
    Metadata
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    • Civil and Environmental Engineering Publications [179]
    • Faculty Publications [4988]
    • Mechanical Engineering Publications [151]

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    Home | FAQ | Contact Us | Privacy Notice | Accessibility Statement
    Managed by the Digital Scholarship Services at Fondren Library, Rice University
    Physical Address: 6100 Main Street, Houston, Texas 77005
    Mailing Address: MS-44, P.O.BOX 1892, Houston, Texas 77251-1892
    Site Map