Damage Identification Scheme Based on Compressive Sensing
- Submitting institution
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The University of Surrey
- Unit of assessment
- 12 - Engineering
- Output identifier
- 9023055_1
- Type
- D - Journal article
- DOI
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10.1061/(ASCE)CP.1943-5487.0000324
- Title of journal
- Journal of Computing in Civil Engineering
- Article number
- -
- First page
- 04014037
- Volume
- 29
- Issue
- 2
- ISSN
- 1943-5487
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2015
- URL
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- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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- Research group(s)
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- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper is recognised as “the first to propose a damage identification scheme based on CS for SHM”, as evidenced in 10.1016/j.ymssp.2016.07.027. Compressive sensing (CS) is a breakthrough technology in signal processing field whose application to structural condition identification, coupled with the idea of using a data dictionary to train the model, led to accurate identification results even in cases with under 10% noise level. The work underpinned successful grant applcations, including ARC DP130104332 and EPSRC EP/R021090/1. It not only led to follow up research, including 10.1016/j.measurement.2017.10.042, but also inspired other researchers in this field, including 10.1177/1475921715604386.
- Author contribution statement
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- Non-English
- No
- English abstract
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