{"id":"https://openalex.org/W4366386386","doi":"https://doi.org/10.1109/tim.2023.3268456","title":"Picture-in-Picture Strategy-Based Complex Graph Neural Network for Remaining Useful Life Prediction of Rotating Machinery","display_name":"Picture-in-Picture Strategy-Based Complex Graph Neural Network for Remaining Useful Life Prediction of Rotating Machinery","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4366386386","doi":"https://doi.org/10.1109/tim.2023.3268456"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3268456","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3268456","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/A5087874502","display_name":"Yudong Cao","orcid":"https://orcid.org/0000-0003-2167-8075"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yudong Cao","raw_affiliation_strings":["School of Mechanical Engineering, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-2167-8075","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051097660","display_name":"Jichao Zhuang","orcid":"https://orcid.org/0000-0002-6681-9145"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jichao Zhuang","raw_affiliation_strings":["School of Mechanical Engineering, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-6681-9145","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029522441","display_name":"Minping Jia","orcid":"https://orcid.org/0000-0001-9010-2307"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minping Jia","raw_affiliation_strings":["School of Mechanical Engineering, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-9010-2307","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045686678","display_name":"Xiaoli Zhao","orcid":"https://orcid.org/0000-0002-9803-4158"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoli Zhao","raw_affiliation_strings":["School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-9803-4158","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029523480","display_name":"Xiaoan Yan","orcid":"https://orcid.org/0000-0001-6986-6943"},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoan Yan","raw_affiliation_strings":["School of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing, China","School of mechanical and electronic engineering, Nanjing Forestry University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-6986-6943","affiliations":[{"raw_affiliation_string":"School of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing, China","institution_ids":["https://openalex.org/I167027274"]},{"raw_affiliation_string":"School of mechanical and electronic engineering, Nanjing Forestry University, Nanjing, China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100423697","display_name":"Zheng Liu","orcid":"https://orcid.org/0000-0002-7241-3483"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]},{"id":"https://openalex.org/I4405260628","display_name":"University of British Columbia, Okanagan Campus","ror":"https://ror.org/04241wz75","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490","https://openalex.org/I4405260628"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Zheng Liu","raw_affiliation_strings":["School of Engineering, University of British Columbia, Kelowna, Canada"],"raw_orcid":"https://orcid.org/0000-0002-7241-3483","affiliations":[{"raw_affiliation_string":"School of Engineering, University of British Columbia, Kelowna, Canada","institution_ids":["https://openalex.org/I141945490","https://openalex.org/I4405260628"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3384,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.78071615,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"72","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T13891","display_name":"Engineering Diagnostics and Reliability","score":0.9427000284194946,"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/T13690","display_name":"Quality and Safety in Healthcare","score":0.9409999847412109,"subfield":{"id":"https://openalex.org/subfields/3607","display_name":"Medical Laboratory Technology"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6163020730018616},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6086433529853821},{"id":"https://openalex.org/keywords/power-graph-analysis","display_name":"Power graph analysis","score":0.5403177738189697},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49378737807273865},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4486331641674042},{"id":"https://openalex.org/keywords/prognostics","display_name":"Prognostics","score":0.4226086735725403},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.42135581374168396},{"id":"https://openalex.org/keywords/topological-graph-theory","display_name":"Topological graph theory","score":0.41036948561668396},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.3872023820877075},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3655816316604614},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34567582607269287},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3425743579864502},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.2840445041656494},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16647496819496155},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.14753872156143188}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6163020730018616},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6086433529853821},{"id":"https://openalex.org/C106937863","wikidata":"https://www.wikidata.org/wiki/Q7236518","display_name":"Power graph analysis","level":3,"score":0.5403177738189697},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49378737807273865},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4486331641674042},{"id":"https://openalex.org/C129364497","wikidata":"https://www.wikidata.org/wiki/Q3042561","display_name":"Prognostics","level":2,"score":0.4226086735725403},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.42135581374168396},{"id":"https://openalex.org/C157406716","wikidata":"https://www.wikidata.org/wiki/Q4115842","display_name":"Topological graph theory","level":5,"score":0.41036948561668396},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.3872023820877075},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3655816316604614},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34567582607269287},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3425743579864502},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.2840445041656494},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16647496819496155},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.14753872156143188},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2023.3268456","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3268456","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":[{"display_name":"Responsible consumption and production","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/12"}],"awards":[{"id":"https://openalex.org/G6920906837","display_name":null,"funder_award_id":"52075095","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2033800551","https://openalex.org/W2523377413","https://openalex.org/W2617137613","https://openalex.org/W2773549135","https://openalex.org/W2809694228","https://openalex.org/W2900438754","https://openalex.org/W2907492528","https://openalex.org/W2917169831","https://openalex.org/W2932010661","https://openalex.org/W2956342231","https://openalex.org/W2977117446","https://openalex.org/W3011667710","https://openalex.org/W3014146531","https://openalex.org/W3021048621","https://openalex.org/W3037944824","https://openalex.org/W3039759439","https://openalex.org/W3116103134","https://openalex.org/W3138116568","https://openalex.org/W3160064936","https://openalex.org/W3173071471","https://openalex.org/W3178034484","https://openalex.org/W3184578020","https://openalex.org/W3212355623","https://openalex.org/W4200473862","https://openalex.org/W4210450738","https://openalex.org/W4221023673","https://openalex.org/W4225709684","https://openalex.org/W4280552892","https://openalex.org/W4280609913","https://openalex.org/W4283741809","https://openalex.org/W4285207637","https://openalex.org/W4285240340","https://openalex.org/W4285245107","https://openalex.org/W4285412600","https://openalex.org/W4293370556","https://openalex.org/W4312537998","https://openalex.org/W4319992826","https://openalex.org/W4321783721","https://openalex.org/W6726873649","https://openalex.org/W6736412012"],"related_works":["https://openalex.org/W2310476526","https://openalex.org/W3213192587","https://openalex.org/W2144291498","https://openalex.org/W2535730979","https://openalex.org/W4368755543","https://openalex.org/W3088104186","https://openalex.org/W1543023114","https://openalex.org/W4245709619","https://openalex.org/W85088162","https://openalex.org/W3004254605"],"abstract_inverted_index":{"Graph":[0],"neural":[1,28,62,100],"networks":[2,29],"are":[3,30],"increasingly":[4],"explored":[5],"in":[6,196],"the":[7,45,55,66,72,85,112,123,130,140,145,160,166,170,176,182],"field":[8],"of":[9,49,54,78,129,144,169,198],"Prognostics":[10],"and":[11,97,142,174,178,201],"Health":[12],"Management":[13],"(PHM)":[14],"due":[15],"to":[16,70,92,105,117,133],"their":[17],"excellent":[18],"performance":[19],"when":[20],"dealing":[21],"with":[22,187],"non-Euclidean":[23],"data.":[24],"However,":[25],"current":[26],"graph":[27,40,61,87,95,99,119,125,132],"mostly":[31],"based":[32,64],"on":[33,44,65,152],"real":[34],"domain":[35,172],"modeling.":[36],"In":[37,52],"addition,":[38],"existing":[39],"construction":[41],"methods":[42,189],"rely":[43],"prior":[46],"positional":[47],"relationship":[48],"multiple":[50],"sensors.":[51],"view":[53],"above,":[56],"this":[57],"paper":[58],"proposes":[59],"complex":[60,94,98,171],"network":[63,101],"picture-in-picture":[67,113],"strategy":[68,114],"(CGNN-PIP)":[69],"realize":[71],"remaining":[73],"useful":[74],"life":[75],"(RUL)":[76],"prediction":[77,199],"rotating":[79],"machinery":[80],"under":[81],"multi-channel":[82],"signals.":[83],"Specifically,":[84],"classical":[86],"convolution":[88],"operation":[89],"is":[90,102,115],"upgraded":[91],"generalized":[93],"convolution,":[96],"further":[103],"constructed":[104],"extract":[106,175],"deep":[107],"degenerate":[108],"feature":[109],"representations.":[110],"Meanwhile,":[111],"designed":[116],"guide":[118],"construction,":[120],"which":[121],"takes":[122],"single-path":[124],"as":[126],"a":[127,135],"node":[128],"new":[131],"build":[134],"deeper-level":[136],"graph.":[137],"We":[138],"verified":[139],"effectiveness":[141],"superiority":[143],"proposed":[146,161],"method":[147],"through":[148],"two":[149],"case":[150],"studies":[151],"different":[153],"run-to-failure":[154],"datasets.":[155],"The":[156,185],"results":[157],"show":[158],"that":[159,192],"CGCN-PIP":[162,193],"can":[163],"reasonably":[164],"construct":[165],"topology":[167],"map":[168],"data,":[173],"temporal":[177],"structural":[179],"information":[180],"reflecting":[181],"equipment":[183],"degradation.":[184],"comparison":[186],"state-of-the-art":[188],"also":[190],"proves":[191],"has":[194],"advantages":[195],"terms":[197],"accuracy":[200],"training":[202],"consumption.":[203]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2025-10-10T00:00:00"}
