{"id":"https://openalex.org/W3088411073","doi":"https://doi.org/10.1109/access.2020.3024544","title":"Direct Connection-Based Convolutional Neural Network (DC-CNN) for Fault Diagnosis of Rotor Systems","display_name":"Direct Connection-Based Convolutional Neural Network (DC-CNN) for Fault Diagnosis of Rotor Systems","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3088411073","doi":"https://doi.org/10.1109/access.2020.3024544","mag":"3088411073"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3024544","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3024544","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09200639.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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://ieeexplore.ieee.org/ielx7/6287639/8948470/09200639.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072782690","display_name":"Myungyon Kim","orcid":"https://orcid.org/0000-0002-3613-4735"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Myungyon Kim","raw_affiliation_strings":["Seoul National University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-3613-4735","affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051700060","display_name":"Joon Ha Jung","orcid":"https://orcid.org/0000-0001-8396-3192"},"institutions":[{"id":"https://openalex.org/I4210111434","display_name":"Korea Institute of Machinery & Materials","ror":"https://ror.org/01qcq9d74","country_code":"KR","type":"facility","lineage":["https://openalex.org/I2801339556","https://openalex.org/I2801339556","https://openalex.org/I4210111434","https://openalex.org/I4210144908","https://openalex.org/I4387152098","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Joon Ha Jung","raw_affiliation_strings":["Korea Institute of Machinery and Materials, Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Institute of Machinery and Materials, Daejeon, South Korea","institution_ids":["https://openalex.org/I4210111434"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040596221","display_name":"Jin Uk Ko","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jin Uk Ko","raw_affiliation_strings":["Seoul National University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-1009-1500","affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085835554","display_name":"Hyeon Bae Kong","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyeon Bae Kong","raw_affiliation_strings":["Seoul National University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100762918","display_name":"Jinwook Lee","orcid":"https://orcid.org/0000-0002-4426-8880"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jinwook Lee","raw_affiliation_strings":["Seoul National University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-4426-8880","affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084771659","display_name":"Byeng D. Youn","orcid":"https://orcid.org/0000-0003-0135-3660"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Byeng Dong Youn","raw_affiliation_strings":["Institute of Advanced Machines and Design, Seoul National University, Seoul, South Korea","OnePredict Inc., Seoul, South Korea","Seoul National University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-0135-3660","affiliations":[{"raw_affiliation_string":"Institute of Advanced Machines and Design, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"OnePredict Inc., Seoul, South Korea","institution_ids":[]},{"raw_affiliation_string":"Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5072782690"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.2732,"has_fulltext":true,"cited_by_count":39,"citation_normalized_percentile":{"value":0.92247098,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"172043","last_page":"172056"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9993000030517578,"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":0.9993000030517578,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.992900013923645,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.983299970626831,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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":0.8146531581878662},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7736972570419312},{"id":"https://openalex.org/keywords/testbed","display_name":"Testbed","score":0.5944300889968872},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.536689281463623},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5341557264328003},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5211420059204102},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4854946434497833},{"id":"https://openalex.org/keywords/rotor","display_name":"Rotor (electric)","score":0.44596779346466064},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.431777685880661},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4208833873271942},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08341646194458008}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8146531581878662},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7736972570419312},{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.5944300889968872},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.536689281463623},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5341557264328003},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5211420059204102},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4854946434497833},{"id":"https://openalex.org/C17281054","wikidata":"https://www.wikidata.org/wiki/Q193466","display_name":"Rotor (electric)","level":2,"score":0.44596779346466064},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.431777685880661},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4208833873271942},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08341646194458008},{"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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","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},{"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3024544","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3024544","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09200639.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:90e2aefc6a054b7c9239a8864a0006d3","is_oa":true,"landing_page_url":"https://doaj.org/article/90e2aefc6a054b7c9239a8864a0006d3","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 172043-172056 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3024544","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3024544","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09200639.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3172982607","display_name":null,"funder_award_id":"2020R1A2C3003644","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G7149071311","display_name":null,"funder_award_id":"R17GA08","funder_id":"https://openalex.org/F4320326258","funder_display_name":"Korea Electric Power Corporation"},{"id":"https://openalex.org/G865754706","display_name":null,"funder_award_id":"2020R1A2C3003644","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320326258","display_name":"Korea Electric Power Corporation","ror":"https://ror.org/04fperw70"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3088411073.pdf","grobid_xml":"https://content.openalex.org/works/W3088411073.grobid-xml"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W640452749","https://openalex.org/W1026270304","https://openalex.org/W1533861849","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1849277567","https://openalex.org/W2033800551","https://openalex.org/W2072713266","https://openalex.org/W2102605133","https://openalex.org/W2107878631","https://openalex.org/W2173008373","https://openalex.org/W2176952908","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2335783338","https://openalex.org/W2520774990","https://openalex.org/W2525778437","https://openalex.org/W2566702409","https://openalex.org/W2754767460","https://openalex.org/W2764024122","https://openalex.org/W2765226309","https://openalex.org/W2768753204","https://openalex.org/W2790390890","https://openalex.org/W2797187289","https://openalex.org/W2807657100","https://openalex.org/W2808496542","https://openalex.org/W2813864053","https://openalex.org/W2887286714","https://openalex.org/W2903312299","https://openalex.org/W2906578288","https://openalex.org/W2909082165","https://openalex.org/W2913289332","https://openalex.org/W2917014261","https://openalex.org/W2919115771","https://openalex.org/W2924922918","https://openalex.org/W2935938728","https://openalex.org/W2939411050","https://openalex.org/W2944544772","https://openalex.org/W2947344279","https://openalex.org/W2949533264","https://openalex.org/W2950621961","https://openalex.org/W2962835968","https://openalex.org/W2962949934","https://openalex.org/W2963446712","https://openalex.org/W2964084166","https://openalex.org/W2964356942","https://openalex.org/W2966040120","https://openalex.org/W2971808039","https://openalex.org/W2989938864","https://openalex.org/W2991223025","https://openalex.org/W3003576014","https://openalex.org/W3020589325","https://openalex.org/W3023396847","https://openalex.org/W3027126966","https://openalex.org/W4388599048","https://openalex.org/W6626481562","https://openalex.org/W6631943919","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6639204139","https://openalex.org/W6748738957","https://openalex.org/W6766252505"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2883256816","https://openalex.org/W2171408034","https://openalex.org/W3003320923","https://openalex.org/W2106140982","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W2350459724"],"abstract_inverted_index":{"Fault":[0],"diagnosis":[1,129],"of":[2,81,104,135,158,175,208,235,239,265],"rotor":[3,191,217],"systems":[4],"is":[5,51,121,210],"important":[6],"to":[7,39,42,53,70,88,99,123,141,184],"prevent":[8,165],"unexpected":[9],"failures.":[10],"Recently,":[11],"deep":[12],"learning":[13],"(DL)":[14],"methods,":[15],"such":[16],"as":[17,94],"a":[18,114,139,216,232],"convolutional":[19],"neural":[20,73,91],"network":[21,92],"(CNN),":[22],"have":[23,67],"been":[24,68],"utilized":[25],"in":[26,101,190],"many":[27,65],"research":[28],"areas,":[29],"including":[30],"fault":[31],"diagnosis.":[32],"DL":[33,61],"has":[34],"gained":[35],"significant":[36,254],"attention":[37],"thanks":[38],"its":[40],"ability":[41],"efficiently":[43],"learn":[44,54,249],"proper":[45],"features":[46,57,242],"from":[47,215],"input":[48],"data.":[49,269],"It":[50],"possible":[52],"enriched":[55],"hierarchical":[56],"by":[58,171],"making":[59],"the":[60,72,77,102,108,143,148,156,162,186,193,224,240,245,257],"architectures":[62,93],"deeper;":[63],"therefore,":[64],"studies":[66],"conducted":[69],"stack":[71],"networks,":[74],"which":[75],"are":[76,180,202],"basic":[78],"building":[79],"blocks":[80],"DL,":[82],"deeper.":[83],"However,":[84],"it":[85],"becomes":[86],"difficult":[87],"comprehensively":[89],"train":[90],"they":[95],"become":[96],"deeper,":[97],"due":[98],"problems":[100,166],"flow":[103,146],"gradient":[105,144],"information":[106,145,201],"during":[107],"training":[109,126],"phase.":[110],"In":[111],"this":[112],"paper,":[113],"direct":[115],"connection":[116],"based":[117],"CNN":[118,140],"(DC-CNN)":[119],"method":[120,226,247,259],"proposed":[122,225,246,258],"significantly":[124],"improve":[125,142],"efficiency":[127],"and":[128,199,204,253],"performance.":[130],"DC-CNN":[131,209],"connects":[132],"feature":[133],"maps":[134],"different":[136],"layers":[137],"within":[138,161],"over":[147],"layers.":[149],"These":[150],"additional":[151],"connections,":[152],"however,":[153],"can":[154,248],"increase":[155],"number":[157,174,234],"trainable":[159],"parameters":[160],"network.":[163],"To":[164],"that":[167,223,244],"might":[168],"be":[169],"caused":[170],"an":[172],"increased":[173],"parameters,":[176],"dimension":[177],"reduction":[178],"modules":[179],"also":[181],"developed.":[182],"Moreover,":[183],"consider":[185],"anisotropic":[187],"characteristics":[188],"inherent":[189],"systems,":[192],"vibration":[194],"images":[195],"containing":[196],"both":[197],"spatial":[198],"temporal":[200],"generated":[203],"utilized.":[205],"The":[206,219],"effectiveness":[207],"validated":[211],"using":[212],"experimental":[213,220],"data":[214],"testbed.":[218],"results":[221],"indicate":[222,243],"outperforms":[227,260],"other":[228,261],"conventional":[229],"approaches":[230,262],"with":[231],"smaller":[233],"parameters.":[236],"Also,":[237],"visualizations":[238],"learned":[241],"much":[250],"more":[251],"effective":[252],"features.":[255],"Furthermore,":[256],"under":[263],"conditions":[264],"insufficient":[266],"or":[267],"noisy":[268]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}