{"id":"https://openalex.org/W2901639182","doi":"https://doi.org/10.1109/access.2018.2880770","title":"A New Transfer Learning Method and its Application on Rotating Machine Fault Diagnosis Under Variant Working Conditions","display_name":"A New Transfer Learning Method and its Application on Rotating Machine Fault Diagnosis Under Variant Working Conditions","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2901639182","doi":"https://doi.org/10.1109/access.2018.2880770","mag":"2901639182"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2880770","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2880770","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2880770","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045175295","display_name":"Weiwei Qian","orcid":"https://orcid.org/0000-0002-1015-7920"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Qian","raw_affiliation_strings":["College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-1015-7920","affiliations":[{"raw_affiliation_string":"College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037433861","display_name":"Shunming Li","orcid":"https://orcid.org/0000-0002-1271-6036"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shunming Li","raw_affiliation_strings":["College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027947686","display_name":"Jinrui Wang","orcid":"https://orcid.org/0000-0001-8690-0672"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinrui Wang","raw_affiliation_strings":["College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9842412"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":8.8045,"has_fulltext":false,"cited_by_count":94,"citation_normalized_percentile":{"value":0.98207151,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"6","issue":null,"first_page":"69907","last_page":"69917"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9987000226974487,"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":0.9987000226974487,"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":0.9864000082015991,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9710000157356262,"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":0.7309417128562927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.664275586605072},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.6074277758598328},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.572468638420105},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5722774267196655},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5361769795417786},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.4962940812110901},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4890021085739136},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.45643723011016846},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.41990718245506287},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4174630641937256},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4161500334739685},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3663550615310669}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7309417128562927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.664275586605072},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.6074277758598328},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.572468638420105},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5722774267196655},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5361769795417786},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.4962940812110901},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4890021085739136},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.45643723011016846},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.41990718245506287},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4174630641937256},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4161500334739685},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3663550615310669},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2880770","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2880770","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5d8dbc36da0d46f7b849b5f052c70241","is_oa":true,"landing_page_url":"https://doaj.org/article/5d8dbc36da0d46f7b849b5f052c70241","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 69907-69917 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2880770","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2880770","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G3178725034","display_name":null,"funder_award_id":"51675262","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W37329324","https://openalex.org/W1589326101","https://openalex.org/W1597576211","https://openalex.org/W1722318740","https://openalex.org/W1965555277","https://openalex.org/W1982696459","https://openalex.org/W1982878030","https://openalex.org/W1985437849","https://openalex.org/W1986614398","https://openalex.org/W1991723619","https://openalex.org/W2036139574","https://openalex.org/W2057266281","https://openalex.org/W2069871951","https://openalex.org/W2072177337","https://openalex.org/W2095307887","https://openalex.org/W2100028154","https://openalex.org/W2115403315","https://openalex.org/W2118045473","https://openalex.org/W2128053425","https://openalex.org/W2159570078","https://openalex.org/W2164943005","https://openalex.org/W2219903032","https://openalex.org/W2237892091","https://openalex.org/W2258884143","https://openalex.org/W2261310161","https://openalex.org/W2293068703","https://openalex.org/W2295125894","https://openalex.org/W2317595875","https://openalex.org/W2395579298","https://openalex.org/W2522389818","https://openalex.org/W2556013418","https://openalex.org/W2562762876","https://openalex.org/W2584994008","https://openalex.org/W2592141621","https://openalex.org/W2610107437","https://openalex.org/W2763583057","https://openalex.org/W2919115771","https://openalex.org/W2963103810","https://openalex.org/W2963217615","https://openalex.org/W2963275094","https://openalex.org/W6601475187","https://openalex.org/W6637542466","https://openalex.org/W6677741084","https://openalex.org/W6685415078","https://openalex.org/W6689917909","https://openalex.org/W6692729736","https://openalex.org/W6697212559","https://openalex.org/W6734335776"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W3108503355","https://openalex.org/W3090555870","https://openalex.org/W3095152779","https://openalex.org/W3119773509","https://openalex.org/W3128220219","https://openalex.org/W3131922633","https://openalex.org/W1487808658","https://openalex.org/W3120400911"],"abstract_inverted_index":{"Effective":[0],"data-driven":[1],"rotating":[2,63],"machine":[3,77],"fault":[4,79,106],"diagnosis":[5,14,80,107],"has":[6],"recently":[7],"been":[8],"a":[9,83,104,168,173],"research":[10],"topic":[11],"in":[12,34,118,188],"the":[13,23,38,54,74,138,155,183],"and":[15,30,66,69,101,134,140,172],"health":[16,159],"management":[17],"of":[18,76,137],"machinery":[19],"systems":[20],"owing":[21],"to":[22,47,112,131,153],"benefits,":[24],"including":[25],"safety":[26],"guarantee,":[27],"labor":[28],"saving,":[29],"reliability":[31],"improvement.":[32],"However,":[33],"vast":[35],"real-world":[36],"applications,":[37],"classifier":[39],"trained":[40],"on":[41,98,167],"one":[42],"dataset":[43,85,171],"will":[44,71],"be":[45,59],"extended":[46],"datasets":[48,57],"under":[49],"variant":[50],"working":[51,113],"conditions.":[52,160],"Meanwhile,":[53],"deviation":[55],"between":[56],"can":[58],"triggered":[60],"easily":[61],"by":[62,165],"speed":[64],"oscillation":[65],"load":[67],"variation,":[68],"it":[70],"highly":[72],"degenerate":[73],"performance":[75,185],"learning-based":[78],"methods.":[81],"Hence,":[82],"novel":[84],"distribution":[86],"discrepancy":[87],"measuring":[88],"algorithm":[89],"called":[90],"high-order":[91],"Kullback-Leibler":[92],"(HKL)":[93],"divergence":[94,100,128,147],"is":[95,110,116,129,148,163,190],"proposed.":[96],"Based":[97],"HKL":[99,127,146],"transfer":[102,179],"learning,":[103],"new":[105],"network":[108],"which":[109,176],"robust":[111],"condition":[114],"variation":[115],"constructed":[117],"this":[119],"paper.":[120],"In":[121,143],"feature":[122,144],"extraction,":[123],"sparse":[124],"filtering":[125],"with":[126,158],"proposed":[130],"learn":[132],"sharing":[133],"discriminative":[135],"features":[136],"source":[139],"target":[141],"domains.":[142],"classification,":[145],"introduced":[149],"into":[150],"softmax":[151],"regression":[152],"link":[154],"domain":[156],"adaptation":[157],"Its":[161],"effectiveness":[162],"verified":[164],"experiments":[166,189],"rolling":[169],"bearing":[170],"gearbox":[174],"dataset,":[175],"include":[177],"18":[178],"learning":[180],"cases.":[181],"Furthermore,":[182],"asymmetrical":[184],"phenomenon":[186],"found":[187],"also":[191],"analyzed.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":21},{"year":2019,"cited_by_count":9}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
