{"id":"https://openalex.org/W2968317349","doi":"https://doi.org/10.1109/tim.2019.2933171","title":"An Iterative Stacking Method for Pipeline Defect Inversion With Complex MFL Signals","display_name":"An Iterative Stacking Method for Pipeline Defect Inversion With Complex MFL Signals","publication_year":2019,"publication_date":"2019-08-14","ids":{"openalex":"https://openalex.org/W2968317349","doi":"https://doi.org/10.1109/tim.2019.2933171","mag":"2968317349"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2019.2933171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2019.2933171","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072406974","display_name":"Ge Yu","orcid":"https://orcid.org/0000-0002-3171-8889"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ge Yu","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100729536","display_name":"Jinhai Liu","orcid":"https://orcid.org/0000-0002-1256-1337"},"institutions":[{"id":"https://openalex.org/I4391767858","display_name":"State Key Laboratory of Synthetical Automation for Process Industries","ror":"https://ror.org/0380ng272","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391767858","https://openalex.org/I9224756"]},{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhai Liu","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, Shenyang, China","State Key Laboratory of Synthetical Automation for Process Industries, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Shenyang, China","institution_ids":["https://openalex.org/I4391767858"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100625792","display_name":"Huaguang Zhang","orcid":"https://orcid.org/0000-0002-2375-9824"},"institutions":[{"id":"https://openalex.org/I4391767858","display_name":"State Key Laboratory of Synthetical Automation for Process Industries","ror":"https://ror.org/0380ng272","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391767858","https://openalex.org/I9224756"]},{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaguang Zhang","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, Shenyang, China","State Key Laboratory of Synthetical Automation for Process Industries, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Shenyang, China","institution_ids":["https://openalex.org/I4391767858"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100322216","display_name":"Chen Liu","orcid":"https://orcid.org/0009-0003-0430-6146"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen Liu","raw_affiliation_strings":["Yale School of Public Health, Yale University, New Haven, USA"],"affiliations":[{"raw_affiliation_string":"Yale School of Public Health, Yale University, New Haven, USA","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5072406974"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":3.5566,"has_fulltext":false,"cited_by_count":57,"citation_normalized_percentile":{"value":0.92759937,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"69","issue":"6","first_page":"3780","last_page":"3788"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12169","display_name":"Non-Destructive Testing Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12169","display_name":"Non-Destructive Testing Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10834","display_name":"Welding Techniques and Residual Stresses","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.6455448865890503},{"id":"https://openalex.org/keywords/magnetic-flux-leakage","display_name":"Magnetic flux leakage","score":0.6413618326187134},{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.6249522566795349},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6032575368881226},{"id":"https://openalex.org/keywords/nondestructive-testing","display_name":"Nondestructive testing","score":0.5462283492088318},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5413017868995667},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.5319749712944031},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4590972065925598},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4512743353843689},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.4311745762825012},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4070969820022583},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3374171555042267},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32419508695602417},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2821034789085388},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1656568944454193},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09163907170295715},{"id":"https://openalex.org/keywords/electromagnetic-coil","display_name":"Electromagnetic coil","score":0.0693482756614685}],"concepts":[{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.6455448865890503},{"id":"https://openalex.org/C20892748","wikidata":"https://www.wikidata.org/wiki/Q4390394","display_name":"Magnetic flux leakage","level":3,"score":0.6413618326187134},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.6249522566795349},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6032575368881226},{"id":"https://openalex.org/C56529433","wikidata":"https://www.wikidata.org/wiki/Q626700","display_name":"Nondestructive testing","level":2,"score":0.5462283492088318},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5413017868995667},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.5319749712944031},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4590972065925598},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4512743353843689},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.4311745762825012},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4070969820022583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3374171555042267},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32419508695602417},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2821034789085388},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1656568944454193},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09163907170295715},{"id":"https://openalex.org/C30403606","wikidata":"https://www.wikidata.org/wiki/Q2981904","display_name":"Electromagnetic coil","level":2,"score":0.0693482756614685},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.0},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2019.2933171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2019.2933171","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2036897366","display_name":null,"funder_award_id":"61627809","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G474394021","display_name":null,"funder_award_id":"2017YFF0108800","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6770382808","display_name":null,"funder_award_id":"61473069","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W1897892887","https://openalex.org/W1974735879","https://openalex.org/W1975096300","https://openalex.org/W1979047002","https://openalex.org/W2009319088","https://openalex.org/W2011382171","https://openalex.org/W2103739184","https://openalex.org/W2160641319","https://openalex.org/W2198235674","https://openalex.org/W2204805460","https://openalex.org/W2279048782","https://openalex.org/W2333090555","https://openalex.org/W2514754851","https://openalex.org/W2526846036","https://openalex.org/W2553446265","https://openalex.org/W2562006333","https://openalex.org/W2562762876","https://openalex.org/W2566875744","https://openalex.org/W2588772229","https://openalex.org/W2595750449","https://openalex.org/W2605049737","https://openalex.org/W2763316552","https://openalex.org/W2794714840","https://openalex.org/W2801659371","https://openalex.org/W2803086989","https://openalex.org/W2805448832","https://openalex.org/W2914208492","https://openalex.org/W2938692364","https://openalex.org/W2963929932","https://openalex.org/W3103826674","https://openalex.org/W6687841705","https://openalex.org/W6729760923"],"related_works":["https://openalex.org/W2035329725","https://openalex.org/W4376641153","https://openalex.org/W2050788868","https://openalex.org/W4250391473","https://openalex.org/W2902977491","https://openalex.org/W2101676717","https://openalex.org/W4241743597","https://openalex.org/W4236534787","https://openalex.org/W2165594630","https://openalex.org/W2577089618"],"abstract_inverted_index":{"Magnetic":[0],"flux":[1],"leakage":[2],"(MFL)":[3],"inspection":[4],"in":[5,13,38,85,120],"nondestructive":[6],"testing":[7],"(NDT)":[8],"has":[9],"been":[10],"widely":[11],"used":[12],"damaged":[14],"pipeline":[15,46],"defect":[16,36,47,101,133],"inversion.":[17],"The":[18],"changeable":[19],"environment":[20],"and":[21,70,87,100,150,155],"the":[22,32,77,93,98,121,125,137,164],"complexity":[23],"of":[24,35,58,132,166],"MFL":[25,144],"signal":[26],"have":[27],"brought":[28],"severe":[29],"challenges":[30],"to":[31,91],"accurate":[33],"estimation":[34,106],"sizes":[37],"inversion":[39,48,134],"issue.":[40,135],"This":[41,55],"article":[42],"proposes":[43],"a":[44,62],"novel":[45],"method":[49,56,138],"(WT-STACK)":[50],"based":[51],"on":[52],"stacking":[53,105],"learning.":[54],"consists":[57],"two":[59],"parts.":[60],"First,":[61],"multi-domain":[63,112],"feature":[64,78,99],"extraction":[65],"with":[66,110,159],"three-axis":[67],"(axial,":[68],"radial,":[69],"circumferential)":[71],"signals":[72,81,145],"is":[73,108,118,139],"constructed.":[74],"To":[75],"avoid":[76],"information":[79],"loss,":[80],"are":[82],"analyzed":[83],"both":[84],"time":[86],"frequency":[88],"domains.":[89],"Second,":[90],"study":[92],"complex":[94],"nonlinear":[95],"relationship":[96],"between":[97],"size,":[102],"an":[103],"iterative":[104],"network":[107],"developed":[109],"dynamic":[111],"features":[113],"input.":[114],"An":[115],"adaptive":[116],"learning":[117],"realized":[119],"network,":[122],"which":[123],"enhances":[124],"generalization":[126],"ability":[127],"for":[128],"different":[129],"sample":[130],"sets":[131],"Finally,":[136],"evaluated":[140],"by":[141],"experiments":[142],"using":[143],"collected":[146],"from":[147],"experimental":[148],"platform":[149],"simulation":[151],"signals.":[152],"Experimental":[153],"results":[154],"comprehensive":[156],"comparison":[157],"analysis":[158],"other":[160],"state-of-art":[161],"methods":[162],"validate":[163],"superiority":[165],"this":[167],"method.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":4}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
