{"id":"https://openalex.org/W4399375631","doi":"https://doi.org/10.1109/icit58233.2024.10540872","title":"Pre-Training Graph Neural Network for Fault Diagnosis and Safety Assessment","display_name":"Pre-Training Graph Neural Network for Fault Diagnosis and Safety Assessment","publication_year":2024,"publication_date":"2024-03-25","ids":{"openalex":"https://openalex.org/W4399375631","doi":"https://doi.org/10.1109/icit58233.2024.10540872"},"language":"en","primary_location":{"id":"doi:10.1109/icit58233.2024.10540872","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icit58233.2024.10540872","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Industrial Technology (ICIT)","raw_type":"proceedings-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/A5046307850","display_name":"Chang Liu","orcid":"https://orcid.org/0000-0002-1674-2995"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chang Liu","raw_affiliation_strings":["Tsinghua University,Department of Automation,Beijing,China","Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Automation,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038690943","display_name":"Xiao He","orcid":"https://orcid.org/0000-0002-4588-0887"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao He","raw_affiliation_strings":["Tsinghua University,Department of Automation,Beijing,China","Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Automation,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046146732","display_name":"Hairong Dong","orcid":"https://orcid.org/0000-0002-7255-2950"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hairong Dong","raw_affiliation_strings":["Beijing Jiaotong University,State Key Laboratory of Advanced Rail Autonomous Operation,Beijing,China","State Key Laboratory of Advanced Rail Autonomous Operation, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University,State Key Laboratory of Advanced Rail Autonomous Operation,Beijing,China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"State Key Laboratory of Advanced Rail Autonomous Operation, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046307850"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08011734,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11357","display_name":"Risk and Safety Analysis","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11357","display_name":"Risk and Safety Analysis","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9876000285148621,"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/T10260","display_name":"Software Engineering Research","score":0.9763000011444092,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7850584387779236},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5655387043952942},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5582886338233948},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5331356525421143},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5309113264083862},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5114408731460571},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5077832341194153},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4659726619720459},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4627193808555603},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.4561126232147217},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45580342411994934},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.42649585008621216},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.42580926418304443},{"id":"https://openalex.org/keywords/safety-monitoring","display_name":"Safety monitoring","score":0.42046040296554565},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.41411611437797546},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12827441096305847},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1265297830104828}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7850584387779236},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5655387043952942},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5582886338233948},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5331356525421143},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5309113264083862},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5114408731460571},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5077832341194153},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4659726619720459},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4627193808555603},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.4561126232147217},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45580342411994934},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.42649585008621216},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.42580926418304443},{"id":"https://openalex.org/C2777488183","wikidata":"https://www.wikidata.org/wiki/Q6900510","display_name":"Safety monitoring","level":2,"score":0.42046040296554565},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.41411611437797546},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12827441096305847},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1265297830104828},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C150903083","wikidata":"https://www.wikidata.org/wiki/Q7108","display_name":"Biotechnology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icit58233.2024.10540872","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icit58233.2024.10540872","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Industrial Technology (ICIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6514885223","display_name":null,"funder_award_id":"61733009,62163012","funder_id":"https://openalex.org/F4320320885","funder_display_name":"European Research Consortium for Informatics and Mathematics"}],"funders":[{"id":"https://openalex.org/F4320320885","display_name":"European Research Consortium for Informatics and Mathematics","ror":"https://ror.org/055zrhj18"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2907492528","https://openalex.org/W2998269939","https://openalex.org/W3012816161","https://openalex.org/W3035725276","https://openalex.org/W3095602948","https://openalex.org/W3129850062","https://openalex.org/W3210535434","https://openalex.org/W3212781537","https://openalex.org/W4200473862","https://openalex.org/W4226303437","https://openalex.org/W4283069194","https://openalex.org/W4285111613","https://openalex.org/W4286359849","https://openalex.org/W4290876096","https://openalex.org/W4312566492","https://openalex.org/W4312641714","https://openalex.org/W4323869169","https://openalex.org/W4366378396","https://openalex.org/W4384916169","https://openalex.org/W4386553343","https://openalex.org/W4387682193","https://openalex.org/W4387717536","https://openalex.org/W4388280264","https://openalex.org/W6766156693","https://openalex.org/W6784694379","https://openalex.org/W6798331393"],"related_works":["https://openalex.org/W2130553454","https://openalex.org/W3022007134","https://openalex.org/W4317548404","https://openalex.org/W3104108945","https://openalex.org/W2033364610","https://openalex.org/W3163689946","https://openalex.org/W2797776314","https://openalex.org/W2153927146","https://openalex.org/W2091066410","https://openalex.org/W4390190783"],"abstract_inverted_index":{"Fault":[0],"diagnosis":[1,110],"and":[2,13,111],"safety":[3,112],"assessment":[4],"are":[5],"two":[6,53],"pivotal":[7],"tasks":[8,55],"for":[9,23,37,51,105],"ensuring":[10],"the":[11,43,57,72,81,92,102,122,125],"reliable":[12],"safe":[14],"operation":[15],"of":[16,31,94,124],"dynamic":[17],"systems.":[18],"Constructing":[19],"separate":[20],"data-driven":[21,49],"models":[22],"each":[24],"task":[25],"usually":[26],"involves":[27],"a":[28,47],"large":[29],"amount":[30],"labeled":[32,103],"data,":[33],"which":[34],"is":[35,60,69,75,88,99],"challenging":[36],"practical":[38],"applications.":[39],"In":[40],"this":[41],"study,":[42],"problem":[44],"that":[45],"building":[46],"unified":[48],"model":[50],"these":[52],"related":[54],"under":[56],"few-shot":[58],"setting":[59],"proposed.":[61],"A":[62,114],"pre-training":[63,82],"graph":[64,78],"neural":[65],"network":[66],"(GNN)":[67],"scheme":[68],"designed.":[70],"Firstly,":[71],"input":[73],"data":[74,104,120],"transformed":[76],"into":[77],"data.":[79],"Then,":[80],"strategy":[83],"based":[84,117],"on":[85,118],"node":[86],"dropping":[87],"employed":[89],"to":[90],"initialize":[91],"parameters":[93],"GNN.":[95],"Finally,":[96],"supervised":[97],"learning":[98],"performed":[100],"using":[101],"downstream":[106],"tasks,":[107],"including":[108],"fault":[109],"assessment.":[113],"case":[115],"study":[116],"bearing":[119],"demonstrates":[121],"effectiveness":[123],"proposed":[126],"scheme.":[127]},"counts_by_year":[],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}
