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Machine vision-based fatigue crack propagation system

dc.contributor.authorGebauer, Jan
dc.contributor.authorŠofer, Pavel
dc.contributor.authorJurek, Martin
dc.contributor.authorWagnerová, Renata
dc.contributor.authorCzebe, Jiří
dc.date.accessioned2022-11-22T08:27:30Z
dc.date.available2022-11-22T08:27:30Z
dc.date.issued2022
dc.identifier.citationSensors. 2022, vol. 22, issue 18, art. no. 6852.cs
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/10084/148900
dc.description.abstractThis paper introduces a machine vision-based system promising low-cost solution for detecting a fatigue crack propagation caused by alternating mechanical stresses. The fatigue crack in technical components usually starts on surfaces at stress concentration points. The presented system was designed to substitute a strain gauge sensor-based measurement using an industrial camera in cooperation with branding software. This paper presents implementation of a machine vision system and algorithm outputs taking on fatigue crack propagation samples.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesSensorscs
dc.relation.urihttps://doi.org/10.3390/s22186852cs
dc.rights© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0cs
dc.subjectcrackcs
dc.subjectpropagationcs
dc.subjectsurface crackcs
dc.subjectmachine visioncs
dc.subjectNational Instrumentscs
dc.subjectVision Buildercs
dc.titleMachine vision-based fatigue crack propagation systemcs
dc.typearticlecs
dc.identifier.doi10.3390/s22186852
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume22cs
dc.description.issue18cs
dc.description.firstpageart. no. 6852cs
dc.identifier.wos000859547900001


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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Kromě případů, kde je uvedeno jinak, licence tohoto záznamu je © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.