{"id":"https://openalex.org/W4225673077","doi":"https://doi.org/10.1109/tii.2022.3165027","title":"A Meta-Learning Method for Electric Machine Bearing Fault Diagnosis Under Varying Working Conditions With Limited Data","display_name":"A Meta-Learning Method for Electric Machine Bearing Fault Diagnosis Under Varying Working Conditions With Limited Data","publication_year":2022,"publication_date":"2022-04-05","ids":{"openalex":"https://openalex.org/W4225673077","doi":"https://doi.org/10.1109/tii.2022.3165027"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2022.3165027","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2022.3165027","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://vbn.aau.dk/ws/files/773739874/A_Meta_Learning_Method_for_Electric_Machine_Bearing_Fault_Diagnosis_under_Varying_Working_Conditions_with_Limited_Data.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100410497","display_name":"Jianjun Chen","orcid":"https://orcid.org/0000-0002-0293-4574"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianjun Chen","raw_affiliation_strings":["School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082636856","display_name":"Weihao Hu","orcid":"https://orcid.org/0000-0002-7019-7289"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihao Hu","raw_affiliation_strings":["School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-7019-7289","affiliations":[{"raw_affiliation_string":"School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100773238","display_name":"Di Cao","orcid":"https://orcid.org/0000-0002-8360-2888"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Cao","raw_affiliation_strings":["School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-8360-2888","affiliations":[{"raw_affiliation_string":"School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062475345","display_name":"Zhenyuan Zhang","orcid":"https://orcid.org/0000-0003-3356-0111"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyuan Zhang","raw_affiliation_strings":["School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-3356-0111","affiliations":[{"raw_affiliation_string":"School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100457678","display_name":"Zhe Chen","orcid":"https://orcid.org/0000-0002-2919-4481"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Zhe Chen","raw_affiliation_strings":["Department of Energy Technology, Aalborg University, Aalborg, Denmark"],"raw_orcid":"https://orcid.org/0000-0002-2919-4481","affiliations":[{"raw_affiliation_string":"Department of Energy Technology, Aalborg University, Aalborg, Denmark","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039395705","display_name":"Frede Blaabjerg","orcid":"https://orcid.org/0000-0001-8311-7412"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Frede Blaabjerg","raw_affiliation_strings":["Department of Energy Technology, Aalborg University, Aalborg, Denmark"],"raw_orcid":"https://orcid.org/0000-0001-8311-7412","affiliations":[{"raw_affiliation_string":"Department of Energy Technology, Aalborg University, Aalborg, Denmark","institution_ids":["https://openalex.org/I891191580"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":14.0315,"has_fulltext":true,"cited_by_count":154,"citation_normalized_percentile":{"value":0.99646294,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"19","issue":"3","first_page":"2552","last_page":"2564"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9984999895095825,"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":0.9984999895095825,"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":0.9919999837875366,"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/T13213","display_name":"Mechanical Failure Analysis and Simulation","score":0.9420999884605408,"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/computer-science","display_name":"Computer science","score":0.6863468289375305},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5999189615249634},{"id":"https://openalex.org/keywords/bearing","display_name":"Bearing (navigation)","score":0.5984029769897461},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.5609421133995056},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5563322305679321},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.500861406326294},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4819912314414978},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4815143048763275},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4220290780067444},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34540754556655884},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21393588185310364},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0834932029247284}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6863468289375305},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5999189615249634},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.5984029769897461},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.5609421133995056},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5563322305679321},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.500861406326294},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4819912314414978},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4815143048763275},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4220290780067444},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34540754556655884},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21393588185310364},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0834932029247284},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tii.2022.3165027","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2022.3165027","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/d0168fc0-096a-4a1e-b709-69ec99814b7b","is_oa":true,"landing_page_url":"https://vbn.aau.dk/da/publications/d0168fc0-096a-4a1e-b709-69ec99814b7b","pdf_url":"https://vbn.aau.dk/ws/files/773739874/A_Meta_Learning_Method_for_Electric_Machine_Bearing_Fault_Diagnosis_under_Varying_Working_Conditions_with_Limited_Data.pdf","source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Chen, J, Hu, W, Cao, D, Zhang, Z, Chen, Z & Blaabjerg, F 2023, 'A Meta-Learning Method for Electric Machine Bearing Fault Diagnosis Under Varying Working Conditions With Limited Data', I E E E Transactions on Industrial Informatics, vol. 19, no. 3, 9749912, pp. 2552 - 2564. https://doi.org/10.1109/TII.2022.3165027","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:publications/d0168fc0-096a-4a1e-b709-69ec99814b7b","is_oa":true,"landing_page_url":"https://vbn.aau.dk/da/publications/d0168fc0-096a-4a1e-b709-69ec99814b7b","pdf_url":"https://vbn.aau.dk/ws/files/773739874/A_Meta_Learning_Method_for_Electric_Machine_Bearing_Fault_Diagnosis_under_Varying_Working_Conditions_with_Limited_Data.pdf","source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Chen, J, Hu, W, Cao, D, Zhang, Z, Chen, Z & Blaabjerg, F 2023, 'A Meta-Learning Method for Electric Machine Bearing Fault Diagnosis Under Varying Working Conditions With Limited Data', I E E E Transactions on Industrial Informatics, vol. 19, no. 3, 9749912, pp. 2552 - 2564. https://doi.org/10.1109/TII.2022.3165027","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4225673077.pdf","grobid_xml":"https://content.openalex.org/works/W4225673077.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1976829994","https://openalex.org/W2036947671","https://openalex.org/W2135139954","https://openalex.org/W2530133016","https://openalex.org/W2584994008","https://openalex.org/W2601590138","https://openalex.org/W2604763608","https://openalex.org/W2740570963","https://openalex.org/W2763269460","https://openalex.org/W2788295705","https://openalex.org/W2887782657","https://openalex.org/W2893747136","https://openalex.org/W2896784509","https://openalex.org/W2897868901","https://openalex.org/W2919115771","https://openalex.org/W2956467153","https://openalex.org/W2967115638","https://openalex.org/W2967625104","https://openalex.org/W2973424371","https://openalex.org/W2990851485","https://openalex.org/W2999650510","https://openalex.org/W3035404531","https://openalex.org/W3040834782","https://openalex.org/W3044844512","https://openalex.org/W3095460974","https://openalex.org/W3108288031","https://openalex.org/W3116698143","https://openalex.org/W3142840631","https://openalex.org/W3174613307","https://openalex.org/W3208853938","https://openalex.org/W4205702529","https://openalex.org/W4294646197","https://openalex.org/W6728255800","https://openalex.org/W6736057607","https://openalex.org/W6750254146"],"related_works":["https://openalex.org/W3162204513","https://openalex.org/W2035937180","https://openalex.org/W2371138613","https://openalex.org/W2048963458","https://openalex.org/W2575656761","https://openalex.org/W2065631063","https://openalex.org/W2378667342","https://openalex.org/W2594567802","https://openalex.org/W2363739414","https://openalex.org/W4283332751"],"abstract_inverted_index":{"Effective":[0],"detection":[1,31],"of":[2,11,19,32,37,78,102,108,148],"fault":[3,33,48,203],"in":[4,34],"rolling":[5,35],"bearings":[6,36],"with":[7,44],"a":[8,25,57,65,70,76,114,145],"limited":[9,45,146],"amount":[10,147],"data":[12,149],"is":[13,54,62,72,92,150],"essential":[14],"for":[15,29,94,206],"the":[16,30,89,106,109,161,169,179,216],"safe":[17],"operation":[18],"electric":[20,38],"machines.":[21],"This":[22,117],"article":[23],"proposes":[24],"novel":[26],"meta-learning-enabled":[27],"method":[28,133,193],"machines":[39],"under":[40,50,82,139,188],"varying":[41],"working":[42,52,84,141,190],"conditions":[43,53,142],"data.":[46],"The":[47,131,175,202],"diagnosis":[49,204],"various":[51,83,140,155,189,224],"cast":[55],"as":[56],"few-shot":[58,129],"classification":[59],"problem,":[60],"which":[61,213],"solved":[63],"using":[64,75],"model-agnostic":[66],"meta-learning-based":[67],"model.":[68],"Specifically,":[69],"meta-learner":[71,110],"first":[73],"trained":[74],"series":[77],"interrelated":[79],"fault-diagnosis":[80],"tasks":[81,125],"conditions.":[85],"During":[86],"this":[87],"stage,":[88],"gradient-by-gradient":[90],"rule":[91],"utilized":[93],"parameter":[95],"optimization":[96],"to":[97,123,223],"achieve":[98,120],"an":[99],"effective":[100],"representation":[101],"these":[103],"tasks.":[104],"Then,":[105],"parameters":[107],"are":[111],"refined":[112],"on":[113,160],"new":[115,124],"task.":[116],"technique":[118],"can":[119,134,219],"fast":[121],"adaptation":[122,200],"by":[126],"utilizing":[127],"only":[128,144],"samples.":[130],"proposed":[132,180,217],"obtain":[135],"high":[136],"fault-detection":[137],"accuracy":[138,205],"when":[143],"available.":[151],"Comparative":[152],"tests":[153],"among":[154],"methods":[156,187],"were":[157],"carried":[158],"out":[159],"Case":[162],"Western":[163],"Reserve":[164],"University":[165,171],"Bearing":[166,173],"Dataset":[167],"and":[168,198],"Paderborn":[170],"Rolling":[172],"Dataset.":[174],"results":[176],"show":[177],"that":[178,215],"model":[181],"performs":[182],"better":[183],"than":[184],"other":[185],"state-of-the-art":[186],"conditions;":[191],"our":[192],"has":[194],"stronger":[195],"generalization":[196],"ability":[197],"faster":[199],"ability.":[201],"both":[207],"datasets":[208],"was":[209],"at":[210],"least":[211],"99%,":[212],"proves":[214],"strategy":[218],"be":[220],"flexibly":[221],"applied":[222],"scenarios.":[225]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":72},{"year":2024,"cited_by_count":42},{"year":2023,"cited_by_count":28},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-10-10T00:00:00"}