Acoustic emission characterisation of two pre-cracked specimens

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dc.contributor.authorGálvez, Antonio
dc.contributor.authorGalar, Diego
dc.contributor.authorAlonso, Asier
dc.contributor.authorErrasti-Alcalá, Borja
dc.contributor.authorBienvenido, Ismael
dc.contributor.authorOrtego, Patxi
dc.contributor.authorJuuso, Esko
dc.contributor.institutionTecnalia Research & Innovation
dc.date.accessioned2024-07-24T11:54:16Z
dc.date.available2024-07-24T11:54:16Z
dc.date.issued2022
dc.descriptionPublisher Copyright: © 2022 18th International Conference on Condition Monitoring and Asset Management, CM 2022. All rights reserved.
dc.description.abstractThis article contains the experiments carried-out to study the capabilities of Acoustic Emissions (AE) in a Ship To Shore (STS) crane. This solution studies the implementation of Structural Health Monitoring (SHM) in an STS crane based on acoustic emissions (AE) technique for detecting cracks and assessing their growth in steel elements subjected to fatigue. The first experiment is performed using a compact tension specimen (CT) made of steel S355 whose dimensions are 125x120x50 mm and its cracks and dimensions are defined based on ASTM and ISO standards. The CT is monitored using AE sensors, and then, the features are extracted from the raw data and used to train, test and validate an unsupervised model. The crack detection model obtains a remarkable accuracy; crack detection at sizing of 3 mm length. As the CT dimensions are small, it is difficult to evaluate the attenuation of AE signals, which is completely necessary for monitoring STS cranes. Therefore, a second experiment is performed using a panel made of steel S355, whose dimensions are 2120x200x8 mm; the panel contains a crack of 50x3 mm. This experiment is performed to analyse the AE signals that come from cracks; specifically, to assess signals attenuation, how the attenuation affects cracks detection in the panel, and features evolution while crack propagation. This is led by monitoring the crack growth with crack detection gauges and installing the AE sensors at different distances of the crack. The assessment is used to develop an unsupervised model to detect cracks and an algorithm for localizing them.en
dc.description.sponsorshipThis project was supported by the Basque Government through HAZITEK (ref. ZL-2021/00452) and by the Spanish Government through the "Centre for the Development of Industrial Technology/CDTI" IDI project (ref: IDI-20210166)
dc.description.statusPeer reviewed
dc.format.extent24
dc.identifier.citationGálvez , A , Galar , D , Alonso , A , Errasti-Alcalá , B , Bienvenido , I , Ortego , P & Juuso , E 2022 , Acoustic emission characterisation of two pre-cracked specimens . in 18th International Conference on Condition Monitoring and Asset Management, CM 2022 . 18th International Conference on Condition Monitoring and Asset Management, CM 2022 , British Institute of Non-Destructive Testing , pp. 87-110 , 18th International Conference on Condition Monitoring and Asset Management, CM 2022 , London , United Kingdom , 7/06/22 .
dc.identifier.citationconference
dc.identifier.isbn9781713862277
dc.identifier.urihttps://hdl.handle.net/11556/2386
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85145879972&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherBritish Institute of Non-Destructive Testing
dc.relation.ispartof18th International Conference on Condition Monitoring and Asset Management, CM 2022
dc.relation.ispartofseries18th International Conference on Condition Monitoring and Asset Management, CM 2022
dc.relation.projectIDSpanish Government
dc.relation.projectIDCentro para el Desarrollo Tecnológico Industrial, CDTI, IDI-20210166
dc.relation.projectIDEusko Jaurlaritza, ZL-2021/00452
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsMechanical Engineering
dc.subject.keywordsSafety, Risk, Reliability and Quality
dc.subject.keywordsIndustrial and Manufacturing Engineering
dc.titleAcoustic emission characterisation of two pre-cracked specimensen
dc.typeconference output
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