A Novel Method for Automatic Defect Classification Using Artificial Neural Networks
| dc.contributor.author | Ghouti, Lahouari | |
| dc.date | 2018-02-14T08:56:19.000 | |
| dc.date.accessioned | 2020-06-30T06:50:20Z | |
| dc.date.available | 2020-06-30T06:50:20Z | |
| dc.date.copyright | Fri Jan 01 00:00:00 UTC 1999 | |
| dc.date.issued | 1999 | |
| dc.description.abstract | <p>Ultrasonic nondestructive evaluation (UNDE) of material aims at the detection of hidden flaws in material is a necessary part of the control of engineering systems for their safe and successful use in practical situations. Conventional UNDE approaches consist of the defect detection, characterization using the human visual inspection. Increasing emphasis on reliability and cost-effective methods of production have motivated a great deal of research in the area of UNDE [1–2]. A typical ultrasonic inspection system is shown in Figure 1.</p> | |
| dc.format.mimetype | application/pdf | |
| dc.identifier | archive/lib.dr.iastate.edu/qnde/1999/allcontent/108/ | |
| dc.identifier.articleid | 3971 | |
| dc.identifier.contextkey | 5820213 | |
| dc.identifier.s3bucket | isulib-bepress-aws-west | |
| dc.identifier.submissionpath | qnde/1999/allcontent/108 | |
| dc.identifier.uri | https://dr.lib.iastate.edu/handle/20.500.12876/61531 | |
| dc.language.iso | en | |
| dc.relation.ispartofseries | Review of Progress in Quantitative Nondestructive Evaluation | |
| dc.source.uri | 10.1007/978-1-4615-4791-4_108 | |
| dc.title | A Novel Method for Automatic Defect Classification Using Artificial Neural Networks | |
| dc.type | event | |
| dc.type.genre | article | |
| dspace.entity.type | Publication | |
| relation.isSeriesOfPublication | 289a28b5-887e-4ddb-8c51-a88d07ebc3f3 |