{"id":"https://openalex.org/W2904737228","doi":"https://doi.org/10.1109/iccais.2018.8570702","title":"Incipient Fault Diagnosis Based on DNN with Transfer Learning","display_name":"Incipient Fault Diagnosis Based on DNN with Transfer Learning","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2904737228","doi":"https://doi.org/10.1109/iccais.2018.8570702","mag":"2904737228"},"language":"en","primary_location":{"id":"doi:10.1109/iccais.2018.8570702","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccais.2018.8570702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Control, Automation and Information Sciences (ICCAIS)","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/A5049901822","display_name":"Danmin Chen","orcid":"https://orcid.org/0000-0003-3133-8277"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Danmin Chen","raw_affiliation_strings":["State Key Laboratory of Mathematical, School of SoftWare Henan University, Kaifeng, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Mathematical, School of SoftWare Henan University, Kaifeng, China","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086263105","display_name":"Shuai Yang","orcid":"https://orcid.org/0000-0001-8836-4236"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Yang","raw_affiliation_strings":["School of Computer and Information, Engineering Henan University, Kaifeng, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information, Engineering Henan University, Kaifeng, China","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079950677","display_name":"Funa Zhou","orcid":"https://orcid.org/0000-0003-3592-9664"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Funa Zhou","raw_affiliation_strings":["School of Computer and Information, Engineering Henan University, Kaifeng, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information, Engineering Henan University, Kaifeng, China","institution_ids":["https://openalex.org/I173899330"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5049901822"],"corresponding_institution_ids":["https://openalex.org/I173899330"],"apc_list":null,"apc_paid":null,"fwci":1.6554,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.85292817,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"303","last_page":"308"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.983299970626831,"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":0.983299970626831,"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":0.9803000092506409,"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":0.9545000195503235,"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/fault","display_name":"Fault (geology)","score":0.7655928134918213},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5893328189849854},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5869268178939819},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5744985342025757},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5171217918395996},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5096852779388428},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48077601194381714},{"id":"https://openalex.org/keywords/fault-model","display_name":"Fault model","score":0.46485698223114014},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43453651666641235},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4100935161113739},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4018968641757965},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34349140524864197},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2395181655883789},{"id":"https://openalex.org/keywords/seismology","display_name":"Seismology","score":0.10616490244865417},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07742780447006226}],"concepts":[{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.7655928134918213},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5893328189849854},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5869268178939819},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5744985342025757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5171217918395996},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5096852779388428},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48077601194381714},{"id":"https://openalex.org/C167391956","wikidata":"https://www.wikidata.org/wiki/Q1401211","display_name":"Fault model","level":3,"score":0.46485698223114014},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43453651666641235},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4100935161113739},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4018968641757965},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34349140524864197},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2395181655883789},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.10616490244865417},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07742780447006226},{"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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccais.2018.8570702","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccais.2018.8570702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Control, Automation and Information Sciences (ICCAIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1968047608","https://openalex.org/W2070808135","https://openalex.org/W2072046589","https://openalex.org/W2083402708","https://openalex.org/W2084041509","https://openalex.org/W2165698076","https://openalex.org/W2552765257","https://openalex.org/W2568819930","https://openalex.org/W2585658440","https://openalex.org/W2610107437","https://openalex.org/W2731372149","https://openalex.org/W2735516492","https://openalex.org/W2748407312","https://openalex.org/W2761753121","https://openalex.org/W2765317657","https://openalex.org/W2770456481","https://openalex.org/W2802012801","https://openalex.org/W2804940842","https://openalex.org/W2884034416","https://openalex.org/W2963088995","https://openalex.org/W2963460810","https://openalex.org/W6750027281"],"related_works":["https://openalex.org/W4206357785","https://openalex.org/W4281381188","https://openalex.org/W2951211570","https://openalex.org/W3192840557","https://openalex.org/W4375928479","https://openalex.org/W3167935049","https://openalex.org/W3023427754","https://openalex.org/W3131673289","https://openalex.org/W4393011546","https://openalex.org/W3198847674"],"abstract_inverted_index":{"Diagnosis":[0],"of":[1,9,40,56,77,85,127,143,168,176],"incipient":[2,66,78,97,108,144,158,169],"fault":[3,24,67,79,90,98,109,120,129,137,145,159,170],"is":[4,29,50,63,172,180],"critical":[5],"for":[6,69,96],"safe":[7],"operation":[8],"the":[10,22,54,150,161,177,184],"system":[11],"because":[12],"it":[13,35,62,133],"can":[14,118,155],"prevent":[15],"disastrous":[16],"accidents":[17],"from":[18],"happening":[19],"by":[20,182],"diagnosing":[21],"early":[23],"before":[25],"deterioration.":[26],"Deep":[27],"learning":[28,153],"efficient":[30],"in":[31,88,123,160],"feature":[32,121,138],"extraction":[33],"but":[34],"requires":[36],"a":[37,73,82,124,140,165],"large":[38,83,125],"number":[39,76,126,142,167],"samples":[41,91,130],"to":[42,65,134],"train":[43],"traditional":[44],"deep":[45],"neural":[46],"network":[47],"(DNN).":[48],"It":[49],"thus":[51],"inevitable":[52],"that":[53],"efficiency":[55,175],"DNN":[57],"will":[58],"be":[59],"affected":[60],"when":[61,163],"applied":[64],"diagnosis":[68,110],"there":[70],"are":[71],"usually":[72],"very":[74],"limited":[75,166],"samples.":[80,146],"Furthermore,":[81],"amount":[84],"information":[86],"involved":[87,122],"significant":[89,128],"was":[92],"not":[93],"adequately":[94],"used":[95],"diagnosis.":[99],"To":[100],"solve":[101],"this":[102,104,148],"problem,":[103],"paper":[105],"proposes":[106],"an":[107],"model":[111,117,179],"with":[112,139],"DNN-based":[113],"transfer":[114,152],"learning.":[115],"The":[116,174],"extract":[119,135],"and":[131],"apply":[132],"insignificant":[136],"small":[141],"In":[147],"way,":[149],"proposed":[151,178],"method":[154],"efficiently":[156],"diagnose":[157],"case":[162],"only":[164],"data":[171,190],"available.":[173],"demonstrated":[181],"utilizing":[183],"Case":[185],"Western":[186],"Reserve":[187],"University":[188],"bearing":[189],"set.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}