{"id":"https://openalex.org/W4404610856","doi":"https://doi.org/10.3390/e26121007","title":"A Real-Time Fault Diagnosis Method for Multi-Source Heterogeneous Information Fusion Based on Two-Level Transfer Learning","display_name":"A Real-Time Fault Diagnosis Method for Multi-Source Heterogeneous Information Fusion Based on Two-Level Transfer Learning","publication_year":2024,"publication_date":"2024-11-22","ids":{"openalex":"https://openalex.org/W4404610856","doi":"https://doi.org/10.3390/e26121007","pmid":"https://pubmed.ncbi.nlm.nih.gov/39766636"},"language":"en","primary_location":{"id":"doi:10.3390/e26121007","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26121007","pdf_url":"https://www.mdpi.com/1099-4300/26/12/1007/pdf?version=1732273155","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/26/12/1007/pdf?version=1732273155","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049901822","display_name":"Danmin Chen","orcid":"https://orcid.org/0000-0003-3133-8277"},"institutions":[{"id":"https://openalex.org/I7726996","display_name":"Henan University of Economic and Law","ror":"https://ror.org/000jtc944","country_code":"CN","type":"education","lineage":["https://openalex.org/I7726996"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danmin Chen","raw_affiliation_strings":["School of Computer and Artificial Intelligence, Henan Finance University, Zhengzhou 450046, China","Zhengzhou Key Laboratory of Financial Big Data Intelligent Application Technology, Zhengzhou 450046, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, Henan Finance University, Zhengzhou 450046, China","institution_ids":["https://openalex.org/I7726996"]},{"raw_affiliation_string":"Zhengzhou Key Laboratory of Financial Big Data Intelligent Application Technology, Zhengzhou 450046, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100346702","display_name":"Zhiqiang Zhang","orcid":"https://orcid.org/0000-0002-0983-3880"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Zhang","raw_affiliation_strings":["School of Logistic Engineering, Shanghai Maritime University, Shanghai 201306, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Logistic Engineering, Shanghai Maritime University, Shanghai 201306, China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079950677","display_name":"Funa Zhou","orcid":"https://orcid.org/0000-0003-3592-9664"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Funa Zhou","raw_affiliation_strings":["School of Logistic Engineering, Shanghai Maritime University, Shanghai 201306, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Logistic Engineering, Shanghai Maritime University, Shanghai 201306, China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114064664","display_name":"Chaoge Wang","orcid":"https://orcid.org/0009-0002-4762-1878"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaoge Wang","raw_affiliation_strings":["School of Logistic Engineering, Shanghai Maritime University, Shanghai 201306, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Logistic Engineering, Shanghai Maritime University, Shanghai 201306, China","institution_ids":["https://openalex.org/I96733725"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5079950677"],"corresponding_institution_ids":["https://openalex.org/I96733725"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":2.1647,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.88111548,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"26","issue":"12","first_page":"1007","last_page":"1007"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.977400004863739,"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":0.977400004863739,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9757999777793884,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9641000032424927,"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/computer-science","display_name":"Computer science","score":0.8174058794975281},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6977326273918152},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6257137656211853},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.6153201460838318},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6014915704727173},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5650036334991455},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5592714548110962},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5437198877334595},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49587640166282654},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.43023058772087097},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42610353231430054},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41192060708999634},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.34596362709999084},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09417980909347534}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8174058794975281},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6977326273918152},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6257137656211853},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.6153201460838318},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6014915704727173},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5650036334991455},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5592714548110962},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5437198877334595},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49587640166282654},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.43023058772087097},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42610353231430054},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41192060708999634},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34596362709999084},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09417980909347534},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/e26121007","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26121007","pdf_url":"https://www.mdpi.com/1099-4300/26/12/1007/pdf?version=1732273155","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:39766636","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39766636","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11675366","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11675366","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11675366/pdf/entropy-26-01007.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:eb114614789a4deba7b2728d95730a72","is_oa":true,"landing_page_url":"https://doaj.org/article/eb114614789a4deba7b2728d95730a72","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":"Entropy, Vol 26, Iss 12, p 1007 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/e26121007","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26121007","pdf_url":"https://www.mdpi.com/1099-4300/26/12/1007/pdf?version=1732273155","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2293218186","display_name":null,"funder_award_id":"2022BS022","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6063553372","display_name":null,"funder_award_id":"232102220022","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7000456721","display_name":null,"funder_award_id":"62073213","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7020612076","display_name":null,"funder_award_id":"232102220022","funder_id":"https://openalex.org/F4320336593","funder_display_name":"Henan Provincial Science and Technology Research Project"},{"id":"https://openalex.org/G8000705819","display_name":null,"funder_award_id":"2022BS022","funder_id":"https://openalex.org/F4320336593","funder_display_name":"Henan Provincial Science and Technology Research Project"},{"id":"https://openalex.org/G8358159851","display_name":null,"funder_award_id":"62073213","funder_id":"https://openalex.org/F4320336593","funder_display_name":"Henan Provincial Science and Technology Research Project"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320336593","display_name":"Henan Provincial Science and Technology Research Project","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4404610856.pdf"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1932847118","https://openalex.org/W2165698076","https://openalex.org/W2395579298","https://openalex.org/W2887782657","https://openalex.org/W2902497325","https://openalex.org/W2912803327","https://openalex.org/W2931331224","https://openalex.org/W2943099062","https://openalex.org/W2971396385","https://openalex.org/W3004931343","https://openalex.org/W3005710163","https://openalex.org/W3005904504","https://openalex.org/W3116400523","https://openalex.org/W3128453436","https://openalex.org/W3142292878","https://openalex.org/W3159732778","https://openalex.org/W4206819248","https://openalex.org/W4214900601","https://openalex.org/W4285157114","https://openalex.org/W4296817697","https://openalex.org/W4304689967","https://openalex.org/W4307568292","https://openalex.org/W4308516234","https://openalex.org/W4312230257","https://openalex.org/W4312250893","https://openalex.org/W4321350102","https://openalex.org/W4322102361","https://openalex.org/W4324291684","https://openalex.org/W4361255950","https://openalex.org/W4385777613","https://openalex.org/W4388076287","https://openalex.org/W4388153530","https://openalex.org/W4388443721","https://openalex.org/W4392163668","https://openalex.org/W4392798869","https://openalex.org/W4392847153","https://openalex.org/W4402043521","https://openalex.org/W6787533553","https://openalex.org/W6847766614"],"related_works":["https://openalex.org/W3000097931","https://openalex.org/W2354322770","https://openalex.org/W4237547500","https://openalex.org/W3183901164","https://openalex.org/W2951211570","https://openalex.org/W2964954556","https://openalex.org/W3135818718","https://openalex.org/W4290188444","https://openalex.org/W2253429366","https://openalex.org/W3127975138"],"abstract_inverted_index":{"A":[0],"convolutional":[1,38,94,141],"neural":[2,39,142,147],"network":[3,110,143],"can":[4],"extract":[5],"features":[6],"from":[7,119,139],"high-dimensional":[8],"data,":[9,82],"but":[10,167],"the":[11,43,120,127,137,152,159,181],"convolution":[12,170],"operation":[13],"has":[14,173],"a":[15,21,29,56,84,107,115,140,145,174,187,191],"high":[16,30],"time":[17,176],"complexity":[18],"and":[19,79,96,135,165,172,190],"requires":[20],"large":[22],"amount":[23],"of":[24,45,112,161,180],"computation.":[25],"For":[26],"equipment":[27],"with":[28],"sampling":[31],"frequency,":[32],"fault":[33,47,57,99,153],"diagnosis":[34,58,154],"methods":[35],"based":[36,65],"on":[37,66],"networks":[40],"cannot":[41],"meet":[42],"requirements":[44],"online":[46],"diagnosis.":[48,100],"To":[49],"solve":[50],"this":[51,53],"problem,":[52],"study":[54],"proposes":[55],"method":[59,71,183],"for":[60,117],"multi-source":[61,76,90],"heterogeneous":[62,77,91],"information":[63,78],"fusion":[64],"two-level":[67,85,150],"transfer":[68,86,118,138],"learning.":[69],"This":[70],"aims":[72],"to":[73,88,105,126,144],"fully":[74],"utilize":[75],"external":[80],"domain":[81],"construct":[83],"mechanism":[87,116],"fuse":[89],"information,":[92],"avoid":[93],"operations,":[95],"achieve":[97],"real-time":[98],"Its":[101],"main":[102],"work":[103],"is":[104,184],"build":[106],"feature":[108,121],"extraction":[109,122],"model":[111,123,130,155],"screenshots,":[113],"design":[114],"using":[124,131,186],"screenshots":[125,166],"deep":[128,146],"learning":[129],"one-dimensional":[132,162],"sequence":[133,163],"signals,":[134],"complete":[136],"network.":[148],"After":[149],"transfer,":[151],"not":[156],"only":[157],"integrates":[158],"characteristics":[160],"signals":[164],"also":[168],"avoids":[169],"operations":[171],"low":[175],"complexity.":[177],"The":[178],"effectiveness":[179],"proposed":[182],"verified":[185],"gearbox":[188],"dataset":[189],"bearing":[192],"dataset.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
