On the Reliability of Automated Analysis of Fracture Surfaces Using a Novel Computer Vision-Based Tool

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dc.date.accessioned2023-12-01T15:33:19Z
dc.date.available2023-12-01T15:33:19Z
dc.date.issued2023-08-05
dc.description.sponsorshipGefördert im Rahmen des Projekts DEALger
dc.identifierdoi:10.17170/kobra-202311159019
dc.identifier.urihttp://hdl.handle.net/123456789/15256
dc.language.isoeng
dc.relation.doidoi:10.1002/adem.202300876
dc.rightsNamensnennung 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectadditive manufacturingeng
dc.subjectimage recognitioneng
dc.subjectobject detectioneng
dc.subjectscanning electron microscopeseng
dc.subjectTi6Al4Veng
dc.subject.ddc620
dc.subject.ddc660
dc.subject.swdRapid Prototyping <Fertigung>ger
dc.subject.swdBruchflächeger
dc.subject.swdBilderkennungger
dc.subject.swdObjekterkennungger
dc.subject.swdRasterelektronenmikroskopger
dc.subject.swdTiAl6V4ger
dc.titleOn the Reliability of Automated Analysis of Fracture Surfaces Using a Novel Computer Vision-Based Tooleng
dc.typeAufsatz
dc.type.versionpublishedVersion
dcterms.abstractFracture surface analysis is of utmost importance with respect to structural integrity of metallic materials. This especially holds true for additively manufactured materials. Despite an increasing trend of automatization of testing methods, the analysis and classification of fatigue fracture surface images is commonly done manually by experts. Although this leads to correct results in most cases, it has several disadvantages, e.g., the need of a huge knowledge base to interpret images correctly. In present work, an unsupervised tool for analysis of overview images of fatigue fracture surface images is developed to support nonexperienced users to identify the origin of the fracture. The tool is developed using fracture surface images of additively manufactured Ti6Al4V specimens fatigued in the high-cycle-fatigue regime and is based on the identification of river marks. Several recording parameters seem to have no significant influence on the results as long as preprocessing settings are adapted. Moreover, it is possible to analyze images of other materials with the tool as long as the fracture surfaces contain river marks. However, special features like multiple origins or origins located in direct vicinity to the surface, e.g., caused by increased plastic strains, require a further tool development or alternative approaches.eng
dcterms.accessRightsopen access
dcterms.creatorEngelhardt, Anna
dcterms.creatorDecke, Jens
dcterms.creatorMeier, David
dcterms.creatorDulig, Franz
dcterms.creatorRagunathan, Rishan
dcterms.creatorWegener, Thomas
dcterms.creatorSick, Bernhard
dcterms.creatorNiendorf, Thomas
dcterms.source.articlenumber2300876
dcterms.source.identifiereissn:1527-2648
dcterms.source.issueIssue 21
dcterms.source.journalAdvanced Engineering Materialseng
dcterms.source.volumeVolume 25
kup.iskupfalse

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