Structural damage detection via combining weighted strategy with trace Lasso.
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| Title: | Structural damage detection via combining weighted strategy with trace Lasso. |
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| Authors: | Chen, Chengbin1, Pan, Chudong1, Chen, Zepeng1, Yu, Ling1,2 lyu1997@163.com |
| Source: | Advances in Structural Engineering. Feb2019, Vol. 22 Issue 3, p597-612. 16p. |
| Subjects: | Technological innovations, Algorithm software, Coefficients (Statistics), Creative ability in technology, Simulation methods & models |
| Abstract: | With the rapid development of computation technologies, swarm intelligence–based algorithms become an innovative technique used for addressing structural damage detection issues, but traditional swarm intelligence–based structural damage detection methods often face with insufficient detection accuracy and lower robustness to noise. As an exploring attempt, a novel structural damage detection method is proposed to tackle the above deficiency via combining weighted strategy with trace least absolute shrinkage and selection operator (Lasso). First, an objective function is defined for the structural damage detection optimization problem by using structural modal parameters; a weighted strategy and the trace Lasso are also involved into the objection function. A novel antlion optimizer algorithm is then employed as a solution solver to the structural damage detection optimization problem. To assess the capability of the proposed structural damage detection method, two numerical simulations and a series of laboratory experiments are performed, and a comparative study on effects of different parameters, such as weighted coefficients, regularization parameters and damage patterns, on the proposed structural damage detection methods are also carried out. Illustrated results show that the proposed structural damage detection method via combining weighted strategy with trace Lasso is able to accurately locate structural damages and quantify damage severities of structures. [ABSTRACT FROM AUTHOR] |
| Copyright of Advances in Structural Engineering is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 134343949 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Structural damage detection via combining weighted strategy with trace Lasso. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Chen%2C+Chengbin%22">Chen, Chengbin</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Pan%2C+Chudong%22">Pan, Chudong</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Chen%2C+Zepeng%22">Chen, Zepeng</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Yu%2C+Ling%22">Yu, Ling</searchLink><relatesTo>1,2</relatesTo><i> lyu1997@163.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Advances+in+Structural+Engineering%22">Advances in Structural Engineering</searchLink>. Feb2019, Vol. 22 Issue 3, p597-612. 16p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Technological+innovations%22">Technological innovations</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithm+software%22">Algorithm software</searchLink><br /><searchLink fieldCode="DE" term="%22Coefficients+%28Statistics%29%22">Coefficients (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Creative+ability+in+technology%22">Creative ability in technology</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: With the rapid development of computation technologies, swarm intelligence–based algorithms become an innovative technique used for addressing structural damage detection issues, but traditional swarm intelligence–based structural damage detection methods often face with insufficient detection accuracy and lower robustness to noise. As an exploring attempt, a novel structural damage detection method is proposed to tackle the above deficiency via combining weighted strategy with trace least absolute shrinkage and selection operator (Lasso). First, an objective function is defined for the structural damage detection optimization problem by using structural modal parameters; a weighted strategy and the trace Lasso are also involved into the objection function. A novel antlion optimizer algorithm is then employed as a solution solver to the structural damage detection optimization problem. To assess the capability of the proposed structural damage detection method, two numerical simulations and a series of laboratory experiments are performed, and a comparative study on effects of different parameters, such as weighted coefficients, regularization parameters and damage patterns, on the proposed structural damage detection methods are also carried out. Illustrated results show that the proposed structural damage detection method via combining weighted strategy with trace Lasso is able to accurately locate structural damages and quantify damage severities of structures. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Advances in Structural Engineering is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1177/1369433218795310 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 597 Subjects: – SubjectFull: Technological innovations Type: general – SubjectFull: Algorithm software Type: general – SubjectFull: Coefficients (Statistics) Type: general – SubjectFull: Creative ability in technology Type: general – SubjectFull: Simulation methods & models Type: general Titles: – TitleFull: Structural damage detection via combining weighted strategy with trace Lasso. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Chen, Chengbin – PersonEntity: Name: NameFull: Pan, Chudong – PersonEntity: Name: NameFull: Chen, Zepeng – PersonEntity: Name: NameFull: Yu, Ling IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2019 Type: published Y: 2019 Identifiers: – Type: issn-print Value: 13694332 Numbering: – Type: volume Value: 22 – Type: issue Value: 3 Titles: – TitleFull: Advances in Structural Engineering Type: main |
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