{"id":"https://openalex.org/W4387519042","doi":"https://doi.org/10.1186/s13634-023-01063-6","title":"A fault diagnosis method for rolling bearings based on graph neural network with one-shot learning","display_name":"A fault diagnosis method for rolling bearings based on graph neural network with one-shot learning","publication_year":2023,"publication_date":"2023-10-11","ids":{"openalex":"https://openalex.org/W4387519042","doi":"https://doi.org/10.1186/s13634-023-01063-6"},"language":"en","primary_location":{"id":"doi:10.1186/s13634-023-01063-6","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-023-01063-6","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-023-01063-6","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-023-01063-6","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102352030","display_name":"Yan Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Gao","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, 400044, China"],"affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, 400044, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101770121","display_name":"Haowei Wu","orcid":"https://orcid.org/0000-0001-5648-8955"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haowei Wu","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, 400044, China"],"affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, 400044, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111054630","display_name":"Haiqian Liao","orcid":null},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiqian Liao","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, 400044, China"],"affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, 400044, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089838274","display_name":"Xu Chen","orcid":"https://orcid.org/0000-0002-0367-3003"},"institutions":[{"id":"https://openalex.org/I145581781","display_name":"Chongqing Technology and Business University","ror":"https://ror.org/05hqf1284","country_code":"CN","type":"education","lineage":["https://openalex.org/I145581781"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Chen","raw_affiliation_strings":["School of Management Science and Engineering, Chongqing Technology and Business University, Chongqing, 400067, China"],"affiliations":[{"raw_affiliation_string":"School of Management Science and Engineering, Chongqing Technology and Business University, Chongqing, 400067, China","institution_ids":["https://openalex.org/I145581781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004009456","display_name":"Shuai Yang","orcid":"https://orcid.org/0000-0001-8015-1578"},"institutions":[{"id":"https://openalex.org/I145581781","display_name":"Chongqing Technology and Business University","ror":"https://ror.org/05hqf1284","country_code":"CN","type":"education","lineage":["https://openalex.org/I145581781"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Yang","raw_affiliation_strings":["National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing, 400067, China"],"affiliations":[{"raw_affiliation_string":"National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing, 400067, China","institution_ids":["https://openalex.org/I145581781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026808051","display_name":"Heng Song","orcid":"https://orcid.org/0000-0001-5592-7063"},"institutions":[{"id":"https://openalex.org/I4210095902","display_name":"China Railway Shanghai Design Institute Group (China)","ror":"https://ror.org/00rhvvr45","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210095902"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Heng Song","raw_affiliation_strings":["Institute of Management Research, China Railway No.4 Engineering Group, Shanghai, 201600, China"],"affiliations":[{"raw_affiliation_string":"Institute of Management Research, China Railway No.4 Engineering Group, Shanghai, 201600, China","institution_ids":["https://openalex.org/I4210095902"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5026808051"],"corresponding_institution_ids":["https://openalex.org/I4210095902"],"apc_list":{"value":1140,"currency":"GBP","value_usd":1398},"apc_paid":{"value":1140,"currency":"GBP","value_usd":1398},"fwci":2.7335,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.90461267,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"2023","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9957000017166138,"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":0.9957000017166138,"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/T11062","display_name":"Gear and Bearing Dynamics Analysis","score":0.991599977016449,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9621000289916992,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7847905158996582},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.630337655544281},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6057692170143127},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5894449949264526},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.5202054381370544},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5142549872398376},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5095203518867493},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4829061031341553},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43025535345077515},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.42726439237594604}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7847905158996582},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.630337655544281},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6057692170143127},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5894449949264526},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.5202054381370544},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5142549872398376},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5095203518867493},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4829061031341553},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43025535345077515},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.42726439237594604},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s13634-023-01063-6","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-023-01063-6","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-023-01063-6","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5485b502e6ab4eecac45adf830e483d0","is_oa":true,"landing_page_url":"https://doaj.org/article/5485b502e6ab4eecac45adf830e483d0","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EURASIP Journal on Advances in Signal Processing, Vol 2023, Iss 1, Pp 1-16 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s13634-023-01063-6","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-023-01063-6","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-023-01063-6","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2697653265","display_name":null,"funder_award_id":"51905058","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320316125","display_name":"China Railway","ror":"https://ror.org/044wv3489"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324805","display_name":"Chongqing Municipal Education Commission","ror":"https://ror.org/031nm5713"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387519042.pdf"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W2074413628","https://openalex.org/W2112796928","https://openalex.org/W2116341502","https://openalex.org/W2164207156","https://openalex.org/W2290847742","https://openalex.org/W2461729787","https://openalex.org/W2593479727","https://openalex.org/W2598587204","https://openalex.org/W2601810159","https://openalex.org/W2606521772","https://openalex.org/W2724754302","https://openalex.org/W2744604411","https://openalex.org/W2744790985","https://openalex.org/W2746111230","https://openalex.org/W2803978172","https://openalex.org/W2908062660","https://openalex.org/W2970796583","https://openalex.org/W2989588046","https://openalex.org/W3027689765","https://openalex.org/W3100157108","https://openalex.org/W3158147183","https://openalex.org/W3196183652","https://openalex.org/W4226220178","https://openalex.org/W4226256575","https://openalex.org/W4286374368","https://openalex.org/W4293412117","https://openalex.org/W4304481542","https://openalex.org/W4385830941","https://openalex.org/W4385934356"],"related_works":["https://openalex.org/W4390516098","https://openalex.org/W4391621807","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W2142795561","https://openalex.org/W4205302943","https://openalex.org/W2561132942","https://openalex.org/W4321487865","https://openalex.org/W3155418658","https://openalex.org/W4383602045"],"abstract_inverted_index":{"Abstract":[0],"The":[1,88],"manuscript":[2],"proposes":[3],"a":[4],"fault":[5],"diagnosis":[6],"method":[7,94,127],"based":[8],"on":[9],"graph":[10],"neural":[11,32,104],"network":[12,33],"(GNN)":[13],"with":[14,77],"one-shot":[15,54],"learning":[16],"to":[17,50],"effectively":[18],"diagnose":[19],"rolling":[20],"bearings":[21],"under":[22],"variable":[23],"operating":[24],"conditions.":[25],"In":[26],"this":[27],"proposed":[28,93,126],"method,":[29],"the":[30,42,92,125],"convolutional":[31],"is":[34,58],"utilized":[35],"for":[36,53],"feature":[37],"extraction,":[38],"reducing":[39],"loss":[40],"in":[41],"process.":[43],"Subsequently,":[44],"GNN":[45],"applies":[46],"an":[47],"adjacency":[48],"matrix":[49],"generate":[51],"codes":[52],"learning.":[55],"Experimental":[56],"verification":[57],"conducted":[59],"using":[60],"open":[61],"data":[62],"from":[63],"Case":[64],"Western":[65],"Reserve":[66],"University":[67],"Rolling":[68],"Bearing":[69],"Data":[70],"Center,":[71],"where":[72],"four":[73],"different":[74],"working":[75],"conditions":[76],"six":[78],"types":[79],"of":[80,91],"typical":[81],"faults":[82],"are":[83,118],"selected":[84],"as":[85,107,120],"input":[86],"signals.":[87],"classification":[89],"accuracy":[90],"reaches":[95],"98.02%.":[96],"To":[97],"further":[98],"validate":[99],"its":[100],"effectiveness,":[101],"traditional":[102],"single-learning":[103],"networks":[105],"such":[106],"Siamese,":[108],"Matching":[109],"Net,":[110],"Prototypical":[111],"Net":[112],"and":[113],"(Stacked":[114],"Auto":[115],"Encoder)":[116],"SAE":[117],"introduced":[119],"comparisons.":[121],"Simulation":[122],"results":[123],"that":[124],"outperforms":[128],"all":[129],"chosen":[130],"methods.":[131]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2025-10-10T00:00:00"}
