{"id":"https://openalex.org/W4321063695","doi":"https://doi.org/10.1109/m2vip55626.2022.10041071","title":"Fault diagnosis of imbalanced multi-channel data based on deep transfer learning","display_name":"Fault diagnosis of imbalanced multi-channel data based on deep transfer learning","publication_year":2022,"publication_date":"2022-11-16","ids":{"openalex":"https://openalex.org/W4321063695","doi":"https://doi.org/10.1109/m2vip55626.2022.10041071"},"language":"en","primary_location":{"id":"doi:10.1109/m2vip55626.2022.10041071","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/m2vip55626.2022.10041071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 28th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","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/A5054633251","display_name":"Yiming Guo","orcid":"https://orcid.org/0000-0002-2634-5651"},"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":true,"raw_author_name":"Yiming Guo","raw_affiliation_strings":["Nanjing University of Science and Technology,School of Mechanical Engineering,Nanjing,China","School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,School of Mechanical Engineering,Nanjing,China","institution_ids":["https://openalex.org/I36399199"]},{"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/A5100357594","display_name":"Xiaoyu Wang","orcid":"https://orcid.org/0000-0002-3819-2015"},"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":"Xiaoyu Wang","raw_affiliation_strings":["Southeast University,School of Mechanical Engineering,Nanjing,China","School of Mechanical Engineering, Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University,School of Mechanical Engineering,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Mechanical Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100643311","display_name":"Zhisheng Zhang","orcid":"https://orcid.org/0000-0002-8084-6270"},"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":"Zhisheng Zhang","raw_affiliation_strings":["Southeast University,School of Mechanical Engineering,Nanjing,China","School of Mechanical Engineering, Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University,School of Mechanical Engineering,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Mechanical Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054633251"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":0.1205,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.45133329,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"9","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9940999746322632,"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":0.9940999746322632,"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/T13429","display_name":"Electricity Theft Detection Techniques","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9868999719619751,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/downtime","display_name":"Downtime","score":0.8858600854873657},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.758615255355835},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.7478713989257812},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6929216384887695},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6498050093650818},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5558235049247742},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5323021411895752},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5081207752227783},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4642307162284851},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46122652292251587},{"id":"https://openalex.org/keywords/fault-model","display_name":"Fault model","score":0.4381861984729767},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.42721840739250183},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3794156610965729},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17613482475280762},{"id":"https://openalex.org/keywords/seismology","display_name":"Seismology","score":0.06789055466651917}],"concepts":[{"id":"https://openalex.org/C180591934","wikidata":"https://www.wikidata.org/wiki/Q1253369","display_name":"Downtime","level":2,"score":0.8858600854873657},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.758615255355835},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7478713989257812},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6929216384887695},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6498050093650818},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5558235049247742},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5323021411895752},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5081207752227783},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4642307162284851},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46122652292251587},{"id":"https://openalex.org/C167391956","wikidata":"https://www.wikidata.org/wiki/Q1401211","display_name":"Fault model","level":3,"score":0.4381861984729767},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.42721840739250183},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3794156610965729},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17613482475280762},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.06789055466651917},{"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C134146338","wikidata":"https://www.wikidata.org/wiki/Q1815901","display_name":"Electronic circuit","level":2,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/m2vip55626.2022.10041071","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/m2vip55626.2022.10041071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 28th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1987216676","https://openalex.org/W2037118876","https://openalex.org/W2070654197","https://openalex.org/W2187089797","https://openalex.org/W2898375427","https://openalex.org/W2915229515","https://openalex.org/W2957568672","https://openalex.org/W2967625104","https://openalex.org/W2969736276","https://openalex.org/W2995758361","https://openalex.org/W3005676037","https://openalex.org/W3015801892","https://openalex.org/W3026405303","https://openalex.org/W3095189068","https://openalex.org/W4206516131"],"related_works":["https://openalex.org/W3183901164","https://openalex.org/W2951211570","https://openalex.org/W3176438653","https://openalex.org/W3135818718","https://openalex.org/W4290188444","https://openalex.org/W3167935049","https://openalex.org/W3003905048","https://openalex.org/W2253429366","https://openalex.org/W3127975138","https://openalex.org/W3171384686"],"abstract_inverted_index":{"The":[0,66,83,96],"fault":[1,15,31,54,72,81,107],"diagnosis":[2,55,73,108],"is":[3,36,89],"an":[4],"effective":[5],"method":[6],"to":[7,29,38,78],"reduce":[8],"downtime":[9],"and":[10,63],"maintenance":[11],"costs.":[12],"However,":[13],"the":[14,30,44,59,71,86,100,111],"samples":[16,35],"obtained":[17],"in":[18,110],"actual":[19],"production":[20],"are":[21],"far":[22],"less":[23],"than":[24],"normal":[25],"samples,":[26,48],"which":[27,57],"leads":[28],"condition":[32],"of":[33,46,85,113],"small":[34,79],"difficult":[37],"be":[39,75],"effectively":[40],"identified.":[41],"To":[42],"solve":[43],"problem":[45],"imbalanced":[47],"this":[49],"paper":[50],"proposes":[51],"a":[52,92],"novel":[53],"model,":[56],"combines":[58],"Convolutional":[60],"Neural":[61],"Network":[62],"transfer":[64,102],"learning.":[65],"proposed":[67,87],"methodology":[68],"can":[69],"make":[70],"model":[74,88,104],"more":[76],"inclined":[77],"sample":[80,114],"data.":[82],"effectiveness":[84],"verified":[90],"by":[91],"real-world":[93],"case":[94,112],"study.":[95],"results":[97],"show":[98],"that":[99],"deep":[101],"learning":[103],"has":[105],"excellent":[106],"performance":[109],"imbalance.":[115]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}
