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A spectral approach for damage quantification in stochastic dynamic systems

M.R. Machado, S. Adhikari, J.M.C. Dos Santos, Sondipon Adhikari

Mechanical Systems and Signal Processing, Volume: 88, Pages: 253 - 273

Swansea University Author: Sondipon Adhikari

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DOI (Published version): 10.1016/j.ymssp.2016.11.018

Abstract

Intrinsic to all real structures, parameter uncertainty can be found in material properties and geometries. Many structural parameters, such as, elastic modulus, Poisson's rate, thickness, density, etc., are spatially distributed by nature. The Karhunen-Loève expansion is a method used to model...

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Published in: Mechanical Systems and Signal Processing
ISSN: 0888-3270
Published: 2017
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URI: https://cronfa.swan.ac.uk/Record/cronfa31349
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first_indexed 2016-12-02T14:29:32Z
last_indexed 2018-02-09T05:18:09Z
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spelling 2017-03-01T11:59:14.6745500 v2 31349 2016-12-02 A spectral approach for damage quantification in stochastic dynamic systems 4ea84d67c4e414f5ccbd7593a40f04d3 Sondipon Adhikari Sondipon Adhikari true false 2016-12-02 FGSEN Intrinsic to all real structures, parameter uncertainty can be found in material properties and geometries. Many structural parameters, such as, elastic modulus, Poisson's rate, thickness, density, etc., are spatially distributed by nature. The Karhunen-Loève expansion is a method used to model the random field expanded in a spectral decomposition. Once many structural parameters can not be modelled as a Gaussian distribution the memoryless nonlinear transformation is used to translate a Gaussian random field in a non-Gaussian. Thus, stochastic methods have been used to include these uncertainties in the structural model. The Spectral Element Method (SEM) is a wave-based numerical approach used to model structures. It is also developed to express parameters as spatially correlated random field in its formulation. In this paper, the problem of structural damage detection under the presence of spatially distributed random parameter is addressed. Explicit equations to localize and assess damage are proposed based on the SEM formulation. Numerical examples in an axially vibrating undamaged and damaged structure with distributed parameters are analysed. Journal Article Mechanical Systems and Signal Processing 88 253 273 0888-3270 1 5 2017 2017-05-01 10.1016/j.ymssp.2016.11.018 COLLEGE NANME Science and Engineering - Faculty COLLEGE CODE FGSEN Swansea University 2017-03-01T11:59:14.6745500 2016-12-02T11:16:43.4584208 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised M.R. Machado 1 S. Adhikari 2 J.M.C. Dos Santos 3 Sondipon Adhikari 4 0031349-03022017155724.pdf machado2016.pdf 2017-02-03T15:57:24.4370000 Output 1423892 application/pdf Accepted Manuscript true 2017-12-01T00:00:00.0000000 false
title A spectral approach for damage quantification in stochastic dynamic systems
spellingShingle A spectral approach for damage quantification in stochastic dynamic systems
Sondipon Adhikari
title_short A spectral approach for damage quantification in stochastic dynamic systems
title_full A spectral approach for damage quantification in stochastic dynamic systems
title_fullStr A spectral approach for damage quantification in stochastic dynamic systems
title_full_unstemmed A spectral approach for damage quantification in stochastic dynamic systems
title_sort A spectral approach for damage quantification in stochastic dynamic systems
author_id_str_mv 4ea84d67c4e414f5ccbd7593a40f04d3
author_id_fullname_str_mv 4ea84d67c4e414f5ccbd7593a40f04d3_***_Sondipon Adhikari
author Sondipon Adhikari
author2 M.R. Machado
S. Adhikari
J.M.C. Dos Santos
Sondipon Adhikari
format Journal article
container_title Mechanical Systems and Signal Processing
container_volume 88
container_start_page 253
publishDate 2017
institution Swansea University
issn 0888-3270
doi_str_mv 10.1016/j.ymssp.2016.11.018
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
document_store_str 1
active_str 0
description Intrinsic to all real structures, parameter uncertainty can be found in material properties and geometries. Many structural parameters, such as, elastic modulus, Poisson's rate, thickness, density, etc., are spatially distributed by nature. The Karhunen-Loève expansion is a method used to model the random field expanded in a spectral decomposition. Once many structural parameters can not be modelled as a Gaussian distribution the memoryless nonlinear transformation is used to translate a Gaussian random field in a non-Gaussian. Thus, stochastic methods have been used to include these uncertainties in the structural model. The Spectral Element Method (SEM) is a wave-based numerical approach used to model structures. It is also developed to express parameters as spatially correlated random field in its formulation. In this paper, the problem of structural damage detection under the presence of spatially distributed random parameter is addressed. Explicit equations to localize and assess damage are proposed based on the SEM formulation. Numerical examples in an axially vibrating undamaged and damaged structure with distributed parameters are analysed.
published_date 2017-05-01T03:38:18Z
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score 11.012678

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