{"id":"https://openalex.org/W2996456528","doi":"https://doi.org/10.1145/3371425.3371463","title":"Health assessment of EMU based on convolutional neural network","display_name":"Health assessment of EMU based on convolutional neural network","publication_year":2019,"publication_date":"2019-12-10","ids":{"openalex":"https://openalex.org/W2996456528","doi":"https://doi.org/10.1145/3371425.3371463","mag":"2996456528"},"language":"en","primary_location":{"id":"doi:10.1145/3371425.3371463","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3371425.3371463","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Artificial Intelligence, Information Processing and Cloud Computing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5111834721","display_name":"Chunyan Liu","orcid":"https://orcid.org/0000-0003-0343-5897"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chunyan Liu","raw_affiliation_strings":["University of Technology HuaXia College, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology HuaXia College, Wuhan, Hubei, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100862633","display_name":"Xiaohong Qian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaohong Qian","raw_affiliation_strings":["University of Technology HuaXia College, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology HuaXia College, Wuhan, Hubei, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9991000294685364,"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":0.9991000294685364,"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/T11062","display_name":"Gear and Bearing Dynamics Analysis","score":0.9879999756813049,"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/T14225","display_name":"Advanced Sensor and Control Systems","score":0.9829999804496765,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8426761031150818},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7115970849990845},{"id":"https://openalex.org/keywords/axle","display_name":"Axle","score":0.6110778450965881},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5557811260223389},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5315067172050476},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5253702402114868},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48016825318336487},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.464163601398468},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4619266390800476},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44088509678840637},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43959885835647583},{"id":"https://openalex.org/keywords/traction-motor","display_name":"Traction motor","score":0.4371633231639862},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3491020202636719},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19462361931800842},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.1279660165309906}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8426761031150818},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7115970849990845},{"id":"https://openalex.org/C129727815","wikidata":"https://www.wikidata.org/wiki/Q188209","display_name":"Axle","level":2,"score":0.6110778450965881},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5557811260223389},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5315067172050476},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5253702402114868},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48016825318336487},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.464163601398468},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4619266390800476},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44088509678840637},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43959885835647583},{"id":"https://openalex.org/C136269787","wikidata":"https://www.wikidata.org/wiki/Q1392476","display_name":"Traction motor","level":2,"score":0.4371633231639862},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3491020202636719},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19462361931800842},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.1279660165309906},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3371425.3371463","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3371425.3371463","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Artificial Intelligence, Information Processing and Cloud Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2126584714","https://openalex.org/W2336464721","https://openalex.org/W2404692435","https://openalex.org/W2480364715","https://openalex.org/W2554375394","https://openalex.org/W2595141258","https://openalex.org/W2727721835","https://openalex.org/W2766203544","https://openalex.org/W2772437201","https://openalex.org/W2897534289","https://openalex.org/W2904284137"],"related_works":["https://openalex.org/W650759427","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W2361325255","https://openalex.org/W3029198973","https://openalex.org/W4400659696","https://openalex.org/W3185156046"],"abstract_inverted_index":{"This":[0,104],"paper":[1],"proposed":[2,118,146],"a":[3],"novel":[4],"intelligent":[5],"fault":[6,76,88,94],"diagnosis":[7,115],"method":[8,105],"to":[9,75,136],"automatically":[10],"identify":[11],"different":[12],"health":[13,21,45,119],"status":[14],"of":[15,31,42,59,85,101,144],"EMU":[16,44],"(Electric":[17],"Multiple":[18],"Units).":[19],"A":[20],"assessment":[22,46,120],"model":[23,121],"was":[24,47,72,96,122],"established":[25],"by":[26,57],"collecting":[27],"the":[28,40,43,51,93,99,102,108,137,142,145],"temperature":[29,53],"data":[30,54],"gear":[32],"box,":[33],"axle":[34],"box":[35],"and":[36,39,90,112,130],"traction":[37],"motor,":[38],"state":[41],"set":[48],"out.":[49],"Firstly,":[50],"collected":[52],"were":[55,81],"processed":[56],"means":[58],"batch":[60],"estimation":[61],"theory":[62],"based":[63],"on":[64],"mean":[65],"finger;":[66],"then,":[67],"CNN":[68,139],"(Convolutional":[69],"Neural":[70],"Network)":[71],"constructed":[73],"according":[74],"categories.":[77],"Finally,":[78],"characteristic":[79],"parameters":[80],"utilized":[82],"as":[83],"input":[84],"CNN,":[86],"after":[87],"analysis":[89,133],"safety":[91],"assessment,":[92],"category":[95],"put":[97],"at":[98],"end":[100],"model.":[103],"greatly":[106],"improved":[107],"feature":[109],"learning":[110],"ability":[111],"enabled":[113],"better":[114],"performance.":[116],"The":[117],"evaluated":[123],"through":[124],"experiments":[125],"using":[126],"Tensorflow.":[127],"Experimental":[128],"results":[129],"comprehensive":[131],"comparison":[132],"with":[134],"respect":[135],"traditional":[138],"had":[140],"demonstrated":[141],"superiority":[143],"method.":[147]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
