Loading…

Fluctuation Analyses for Pattern Classification in Nondestructive Materials Inspection

We review recent work on the application of fluctuation analyses of time series for pattern classification in nondestructive materials inspection. These analyses are based on the evaluation of time-series fluctuations across time intervals of increasing size, and were originally introduced in the st...

Full description

Saved in:
Bibliographic Details
Published in:EURASIP journal on advances in signal processing 2010-01, Vol.2010 (1), Article 262869
Main Authors: Vieira, A P, de Moura, E P, Gonçalves, L L
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c406t-1e383b36275e98d5a51f60a3a92eca728b64ff68108b5659099054060a1896873
cites cdi_FETCH-LOGICAL-c406t-1e383b36275e98d5a51f60a3a92eca728b64ff68108b5659099054060a1896873
container_end_page
container_issue 1
container_start_page
container_title EURASIP journal on advances in signal processing
container_volume 2010
creator Vieira, A P
de Moura, E P
Gonçalves, L L
description We review recent work on the application of fluctuation analyses of time series for pattern classification in nondestructive materials inspection. These analyses are based on the evaluation of time-series fluctuations across time intervals of increasing size, and were originally introduced in the study of fractals. A number of examples indicate that this approach yields relevant features allowing the successful classification of patterns such as (i) microstructure signatures in cast irons, as probed by backscattered ultrasonic signals; (ii) welding defects in metals, as probed by TOFD ultrasonic signals; (iii) gear faults, based on vibration signals; (iv) weld-transfer modes, as probed by voltage and current time series; (v) microstructural composition in stainless steel, as probed by magnetic Barkhausen noise and magnetic flux signals.
doi_str_mv 10.1155/2010/262869
format article
fullrecord <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_65ef33943b2f47e5a26459ec231de745</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_65ef33943b2f47e5a26459ec231de745</doaj_id><sourcerecordid>1671610587</sourcerecordid><originalsourceid>FETCH-LOGICAL-c406t-1e383b36275e98d5a51f60a3a92eca728b64ff68108b5659099054060a1896873</originalsourceid><addsrcrecordid>eNptkU1LAzEQhhdRsH6c_AN7FLSaj002OZZitVA_Duo1TNOJpGw3NdkV_PemrogHTzMMz7zDO29RnFFyRakQ14xQcs0kU1LvFSMqVT2WVJH9P_1hcZTSmhAhGWGj4nXW9LbrofOhLSctNJ8JU-lCLJ-g6zC25bSBlLzzdmB8Wz6EdoWpi3nRf2B5D5nz0KRy3qYt2h12Uhy4PMHTn3pcvMxunqd348Xj7Xw6WYxtRWQ3psgVX3LJaoFarQQI6iQBDpqhhZqppayck4oStRRSaKI1EXmTAFU6O-LHxXzQXQVYm230G4ifJoA334MQ3wzEztsGjRToONcVXzJX1SiAyUpotIzTFdaVyFrng9Y2hvc-GzQbnyw2DbQY-mSorKmkRHyfvRhQG0NKEd3vaUrMLgmzS8IMSWT6cqBTpto3jGYd-ph_nf7FvwDHN4eF</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1671610587</pqid></control><display><type>article</type><title>Fluctuation Analyses for Pattern Classification in Nondestructive Materials Inspection</title><source>Publicly Available Content Database</source><source>Springer Nature - SpringerLink Journals - Fully Open Access </source><creator>Vieira, A P ; de Moura, E P ; Gonçalves, L L</creator><creatorcontrib>Vieira, A P ; de Moura, E P ; Gonçalves, L L</creatorcontrib><description>We review recent work on the application of fluctuation analyses of time series for pattern classification in nondestructive materials inspection. These analyses are based on the evaluation of time-series fluctuations across time intervals of increasing size, and were originally introduced in the study of fractals. A number of examples indicate that this approach yields relevant features allowing the successful classification of patterns such as (i) microstructure signatures in cast irons, as probed by backscattered ultrasonic signals; (ii) welding defects in metals, as probed by TOFD ultrasonic signals; (iii) gear faults, based on vibration signals; (iv) weld-transfer modes, as probed by voltage and current time series; (v) microstructural composition in stainless steel, as probed by magnetic Barkhausen noise and magnetic flux signals.</description><identifier>ISSN: 1687-6180</identifier><identifier>ISSN: 1687-6172</identifier><identifier>EISSN: 1687-6180</identifier><identifier>DOI: 10.1155/2010/262869</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Classification ; Engineering ; Fluctuation ; Fractal analysis ; Inspection ; Microstructure ; Quantum Information Technology ; Review Article ; Signal Processing in Advanced Nondestructive Materials Inspection ; Signal,Image and Speech Processing ; Signatures ; Spintronics ; Time series ; Ultrasonic testing ; Weld defects</subject><ispartof>EURASIP journal on advances in signal processing, 2010-01, Vol.2010 (1), Article 262869</ispartof><rights>Vieira et al. 2010. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c406t-1e383b36275e98d5a51f60a3a92eca728b64ff68108b5659099054060a1896873</citedby><cites>FETCH-LOGICAL-c406t-1e383b36275e98d5a51f60a3a92eca728b64ff68108b5659099054060a1896873</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925,37013</link.rule.ids></links><search><creatorcontrib>Vieira, A P</creatorcontrib><creatorcontrib>de Moura, E P</creatorcontrib><creatorcontrib>Gonçalves, L L</creatorcontrib><title>Fluctuation Analyses for Pattern Classification in Nondestructive Materials Inspection</title><title>EURASIP journal on advances in signal processing</title><addtitle>EURASIP J. Adv. Signal Process</addtitle><description>We review recent work on the application of fluctuation analyses of time series for pattern classification in nondestructive materials inspection. These analyses are based on the evaluation of time-series fluctuations across time intervals of increasing size, and were originally introduced in the study of fractals. A number of examples indicate that this approach yields relevant features allowing the successful classification of patterns such as (i) microstructure signatures in cast irons, as probed by backscattered ultrasonic signals; (ii) welding defects in metals, as probed by TOFD ultrasonic signals; (iii) gear faults, based on vibration signals; (iv) weld-transfer modes, as probed by voltage and current time series; (v) microstructural composition in stainless steel, as probed by magnetic Barkhausen noise and magnetic flux signals.</description><subject>Classification</subject><subject>Engineering</subject><subject>Fluctuation</subject><subject>Fractal analysis</subject><subject>Inspection</subject><subject>Microstructure</subject><subject>Quantum Information Technology</subject><subject>Review Article</subject><subject>Signal Processing in Advanced Nondestructive Materials Inspection</subject><subject>Signal,Image and Speech Processing</subject><subject>Signatures</subject><subject>Spintronics</subject><subject>Time series</subject><subject>Ultrasonic testing</subject><subject>Weld defects</subject><issn>1687-6180</issn><issn>1687-6172</issn><issn>1687-6180</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNptkU1LAzEQhhdRsH6c_AN7FLSaj002OZZitVA_Duo1TNOJpGw3NdkV_PemrogHTzMMz7zDO29RnFFyRakQ14xQcs0kU1LvFSMqVT2WVJH9P_1hcZTSmhAhGWGj4nXW9LbrofOhLSctNJ8JU-lCLJ-g6zC25bSBlLzzdmB8Wz6EdoWpi3nRf2B5D5nz0KRy3qYt2h12Uhy4PMHTn3pcvMxunqd348Xj7Xw6WYxtRWQ3psgVX3LJaoFarQQI6iQBDpqhhZqppayck4oStRRSaKI1EXmTAFU6O-LHxXzQXQVYm230G4ifJoA334MQ3wzEztsGjRToONcVXzJX1SiAyUpotIzTFdaVyFrng9Y2hvc-GzQbnyw2DbQY-mSorKmkRHyfvRhQG0NKEd3vaUrMLgmzS8IMSWT6cqBTpto3jGYd-ph_nf7FvwDHN4eF</recordid><startdate>20100101</startdate><enddate>20100101</enddate><creator>Vieira, A P</creator><creator>de Moura, E P</creator><creator>Gonçalves, L L</creator><general>Springer International Publishing</general><general>SpringerOpen</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>DOA</scope></search><sort><creationdate>20100101</creationdate><title>Fluctuation Analyses for Pattern Classification in Nondestructive Materials Inspection</title><author>Vieira, A P ; de Moura, E P ; Gonçalves, L L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c406t-1e383b36275e98d5a51f60a3a92eca728b64ff68108b5659099054060a1896873</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Classification</topic><topic>Engineering</topic><topic>Fluctuation</topic><topic>Fractal analysis</topic><topic>Inspection</topic><topic>Microstructure</topic><topic>Quantum Information Technology</topic><topic>Review Article</topic><topic>Signal Processing in Advanced Nondestructive Materials Inspection</topic><topic>Signal,Image and Speech Processing</topic><topic>Signatures</topic><topic>Spintronics</topic><topic>Time series</topic><topic>Ultrasonic testing</topic><topic>Weld defects</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vieira, A P</creatorcontrib><creatorcontrib>de Moura, E P</creatorcontrib><creatorcontrib>Gonçalves, L L</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>EURASIP journal on advances in signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vieira, A P</au><au>de Moura, E P</au><au>Gonçalves, L L</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fluctuation Analyses for Pattern Classification in Nondestructive Materials Inspection</atitle><jtitle>EURASIP journal on advances in signal processing</jtitle><stitle>EURASIP J. Adv. Signal Process</stitle><date>2010-01-01</date><risdate>2010</risdate><volume>2010</volume><issue>1</issue><artnum>262869</artnum><issn>1687-6180</issn><issn>1687-6172</issn><eissn>1687-6180</eissn><abstract>We review recent work on the application of fluctuation analyses of time series for pattern classification in nondestructive materials inspection. These analyses are based on the evaluation of time-series fluctuations across time intervals of increasing size, and were originally introduced in the study of fractals. A number of examples indicate that this approach yields relevant features allowing the successful classification of patterns such as (i) microstructure signatures in cast irons, as probed by backscattered ultrasonic signals; (ii) welding defects in metals, as probed by TOFD ultrasonic signals; (iii) gear faults, based on vibration signals; (iv) weld-transfer modes, as probed by voltage and current time series; (v) microstructural composition in stainless steel, as probed by magnetic Barkhausen noise and magnetic flux signals.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1155/2010/262869</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1687-6180
ispartof EURASIP journal on advances in signal processing, 2010-01, Vol.2010 (1), Article 262869
issn 1687-6180
1687-6172
1687-6180
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_65ef33943b2f47e5a26459ec231de745
source Publicly Available Content Database; Springer Nature - SpringerLink Journals - Fully Open Access
subjects Classification
Engineering
Fluctuation
Fractal analysis
Inspection
Microstructure
Quantum Information Technology
Review Article
Signal Processing in Advanced Nondestructive Materials Inspection
Signal,Image and Speech Processing
Signatures
Spintronics
Time series
Ultrasonic testing
Weld defects
title Fluctuation Analyses for Pattern Classification in Nondestructive Materials Inspection
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-30T19%3A13%3A35IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Fluctuation%20Analyses%20for%20Pattern%20Classification%20in%20Nondestructive%20Materials%20Inspection&rft.jtitle=EURASIP%20journal%20on%20advances%20in%20signal%20processing&rft.au=Vieira,%20A%20P&rft.date=2010-01-01&rft.volume=2010&rft.issue=1&rft.artnum=262869&rft.issn=1687-6180&rft.eissn=1687-6180&rft_id=info:doi/10.1155/2010/262869&rft_dat=%3Cproquest_doaj_%3E1671610587%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c406t-1e383b36275e98d5a51f60a3a92eca728b64ff68108b5659099054060a1896873%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1671610587&rft_id=info:pmid/&rfr_iscdi=true