Automatic defect recognition in corrosion logging using magnetic imaging defectoscopy data

dc.contributor.author	Gaibadullina R.
dc.contributor.author	Zagidullin B.
dc.contributor.author	Bochkarev V.
dc.date.accessioned	2018-09-18T20:24:05Z
dc.date.available	2018-09-18T20:24:05Z
dc.date.issued	2014
dc.identifier.issn	1613-0073
dc.identifier.uri	https://dspace.kpfu.ru/xmlui/handle/net/139497
dc.description.abstract	The Magnetic Imaging Defectoscopy is designed for detection of corrosion zones in oil wells. Location of corrosion zones is a time-consuming process, during which some defects can be missed. Therefore this process shall be automated. This document describes an algorithm of automatic defect recognition based on maximum likelihood criterion and the use of wavelet threshold processing for noise reduction and pre-conditioning of experimental data.
dc.relation.ispartofseries	CEUR Workshop Proceedings
dc.subject	Magnetic imaging defectoscopy (MID)
dc.subject	Maximum likelihood criterion
dc.subject	Wavelet filtering
dc.title	Automatic defect recognition in corrosion logging using magnetic imaging defectoscopy data
dc.type	Conference Paper
dc.relation.ispartofseries-volume	1197
dc.collection	Публикации сотрудников КФУ
dc.relation.startpage	86
dc.source.id	SCOPUS16130073-2014-1197-SID84925278530

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Публикации сотрудников КФУ Scopus [24551]
Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.