A Systematic Approach to Ultrasonic Pattern Recognition for Real-Time Intelligent Flaw Classification in Weldments

dc.contributor.author Song, Sung-Jin
dc.contributor.author Kim, Hak-Joon
dc.contributor.author Lee, Hyun
dc.date 2018-02-14T08:56:40.000
dc.date.accessioned 2020-06-30T06:50:22Z
dc.date.available 2020-06-30T06:50:22Z
dc.date.copyright Fri Jan 01 00:00:00 UTC 1999
dc.date.issued 1999
dc.description.abstract <p>Flaw classification is one of the essential issues in quantitative ultrasonic nondestructive evaluation of weldments. Ultrasonic flaw classification can be divided into three approaches [1]; 1) conventional approaches which use heuristic experience-based echo-dynamic pattern identification techniques, 2) model-based approaches which use model-based strong features in ultrasonic flaw signals, and 3) ultrasonic pattern recognition approaches which use features and decision making algorithms and adopt various signal processing techniques and artificial intelligent tools. Among these approaches, ultrasonic pattern recognition approaches which are considered as the most promising tool have been investigated extensively in the ultrasonic nondestructive evaluation (NDE) community [2–6].</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/qnde/1999/allcontent/111/
dc.identifier.articleid 3974
dc.identifier.contextkey 5820218
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath qnde/1999/allcontent/111
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/61535
dc.language.iso en
dc.relation.ispartofseries Review of Progress in Quantitative Nondestructive Evaluation
dc.source.uri 10.1007/978-1-4615-4791-4_111
dc.title A Systematic Approach to Ultrasonic Pattern Recognition for Real-Time Intelligent Flaw Classification in Weldments
dc.type event
dc.type.genre article
dspace.entity.type Publication
relation.isSeriesOfPublication 289a28b5-887e-4ddb-8c51-a88d07ebc3f3
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