{"id":"https://openalex.org/W3120487494","doi":"https://doi.org/10.1109/tim.2020.3047922","title":"Fault Diagnosis of High-Speed Train Bogie Based on the Improved-CEEMDAN and 1-D CNN Algorithms","display_name":"Fault Diagnosis of High-Speed Train Bogie Based on the Improved-CEEMDAN and 1-D CNN Algorithms","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3120487494","doi":"https://doi.org/10.1109/tim.2020.3047922","mag":"3120487494"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2020.3047922","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.3047922","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-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/A5032642266","display_name":"Deqing Huang","orcid":"https://orcid.org/0000-0002-8185-9030"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Deqing Huang","raw_affiliation_strings":["Institute of Systems Science and Technology, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Institute of Systems Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057399926","display_name":"Shupan Li","orcid":"https://orcid.org/0000-0001-8792-4908"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shupan Li","raw_affiliation_strings":["Institute of Systems Science and Technology, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Institute of Systems Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004921838","display_name":"Na Qin","orcid":"https://orcid.org/0000-0003-0473-6640"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Na Qin","raw_affiliation_strings":["Institute of Systems Science and Technology, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Institute of Systems Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101872590","display_name":"Yuanjie Zhang","orcid":"https://orcid.org/0000-0003-0101-9670"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanjie Zhang","raw_affiliation_strings":["Institute of Systems Science and Technology, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Institute of Systems Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5032642266"],"corresponding_institution_ids":["https://openalex.org/I4800084"],"apc_list":null,"apc_paid":null,"fwci":12.8604,"has_fulltext":false,"cited_by_count":116,"citation_normalized_percentile":{"value":0.99255846,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"70","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9983999729156494,"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":0.9983999729156494,"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/T10842","display_name":"Railway Engineering and Dynamics","score":0.982200026512146,"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/T11062","display_name":"Gear and Bearing Dynamics Analysis","score":0.9416000247001648,"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/bogie","display_name":"Bogie","score":0.9645748138427734},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.8153539896011353},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7564284205436707},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.704291045665741},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5845562815666199},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.572710394859314},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5227632522583008},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5193225145339966},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47382935881614685},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4706622362136841},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4674775302410126},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.42675548791885376},{"id":"https://openalex.org/keywords/vibration","display_name":"Vibration","score":0.41708552837371826},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41081929206848145},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.33040159940719604},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32680538296699524},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.1182299256324768},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.11340487003326416},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.11223506927490234},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08356621861457825},{"id":"https://openalex.org/keywords/seismology","display_name":"Seismology","score":0.08028876781463623},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07928627729415894}],"concepts":[{"id":"https://openalex.org/C123045823","wikidata":"https://www.wikidata.org/wiki/Q217421","display_name":"Bogie","level":2,"score":0.9645748138427734},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.8153539896011353},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7564284205436707},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.704291045665741},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5845562815666199},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.572710394859314},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5227632522583008},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5193225145339966},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47382935881614685},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4706622362136841},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4674775302410126},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.42675548791885376},{"id":"https://openalex.org/C198394728","wikidata":"https://www.wikidata.org/wiki/Q3695508","display_name":"Vibration","level":2,"score":0.41708552837371826},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41081929206848145},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.33040159940719604},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32680538296699524},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.1182299256324768},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.11340487003326416},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.11223506927490234},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08356621861457825},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.08028876781463623},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07928627729415894},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2020.3047922","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.3047922","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4065389682","display_name":null,"funder_award_id":"U1934221","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4679897899","display_name":null,"funder_award_id":"61773323","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5097918705","display_name":null,"funder_award_id":"2019YJ0210","funder_id":"https://openalex.org/F4320333335","funder_display_name":"Sichuan Province Science and Technology Support Program"},{"id":"https://openalex.org/G802556646","display_name":null,"funder_award_id":"61733015","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320333335","display_name":"Sichuan Province Science and Technology Support Program","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1997088636","https://openalex.org/W2007221293","https://openalex.org/W2009465763","https://openalex.org/W2009822615","https://openalex.org/W2014506068","https://openalex.org/W2120390927","https://openalex.org/W2125056386","https://openalex.org/W2321536237","https://openalex.org/W2357119592","https://openalex.org/W2461729787","https://openalex.org/W2552774073","https://openalex.org/W2574952845","https://openalex.org/W2581853886","https://openalex.org/W2582337578","https://openalex.org/W2593479727","https://openalex.org/W2594265129","https://openalex.org/W2595141258","https://openalex.org/W2730293128","https://openalex.org/W2768753204","https://openalex.org/W2807874407","https://openalex.org/W2884367402","https://openalex.org/W2896827919","https://openalex.org/W2897647261","https://openalex.org/W2897868901","https://openalex.org/W2899412293","https://openalex.org/W2902814948","https://openalex.org/W2905949437","https://openalex.org/W2918117471","https://openalex.org/W2919115771","https://openalex.org/W2922660557","https://openalex.org/W2933532955","https://openalex.org/W2940908842","https://openalex.org/W2948018258","https://openalex.org/W2948899061","https://openalex.org/W2953212672","https://openalex.org/W2964121744","https://openalex.org/W2965713442","https://openalex.org/W2972592847","https://openalex.org/W2980201327","https://openalex.org/W2981724826","https://openalex.org/W3000813703","https://openalex.org/W3005858530","https://openalex.org/W3006824265","https://openalex.org/W3046248607","https://openalex.org/W3086994053","https://openalex.org/W3089171422","https://openalex.org/W6631190155","https://openalex.org/W6783857909","https://openalex.org/W6991192723"],"related_works":["https://openalex.org/W2359262815","https://openalex.org/W2811390910","https://openalex.org/W2146076056","https://openalex.org/W154259412","https://openalex.org/W4312376745","https://openalex.org/W2913302899","https://openalex.org/W2767651786","https://openalex.org/W2144059113","https://openalex.org/W3003836766","https://openalex.org/W1964120219"],"abstract_inverted_index":{"Realizing":[0],"the":[1,16,31,39,48,67,80,83,94,98,102,110,114,127,144,147,153,156,167],"accurate":[2],"fault":[3,26,32,95,119],"diagnosis":[4,27],"of":[5,11,19,34,41,47,86,97,126,146,158],"high-speed":[6],"train":[7],"(HST)":[8],"bogie":[9,36,136],"is":[10,71,106,130],"great":[12],"significance":[13],"for":[14],"ensuring":[15],"safe":[17],"operation":[18],"HSTs.":[20],"This":[21],"article":[22],"proposes":[23],"a":[24],"novel":[25],"method":[28,129,149],"to":[29,108,117],"identify":[30],"states":[33],"HST":[35,99],"and":[37,59,121,132,155,176,186],"localize":[38],"positions":[40],"faulty":[42,159],"components":[43,85,116],"simultaneously":[44],"by":[45,89,166],"virtue":[46],"improved":[49],"complete":[50],"ensemble":[51],"empirical":[52],"mode":[53,76],"decomposition":[54],"with":[55,171],"adaptive":[56],"noise":[57],"(ICEEMDAN)":[58],"1-D":[60,103],"convolutional":[61,182],"neural":[62,184],"network":[63],"(1-D":[64],"CNN).":[65],"First,":[66],"raw":[68],"vibration":[69],"signal":[70],"decomposed":[72],"into":[73],"multiple":[74],"intrinsic":[75],"functions":[77],"(IMFs)":[78],"via":[79],"ICEEMDAN.":[81],"Then,":[82],"high-frequency":[84,115],"IMFs":[87],"obtained":[88],"ICEEMDAN":[90],"are":[91],"selected":[92],"as":[93],"features":[96,112],"bogie.":[100],"Afterward,":[101],"CNN":[104],"model":[105],"adopted":[107],"learn":[109],"deeper":[111],"from":[113],"conduct":[118],"classification":[120],"localization.":[122],"The":[123],"prediction":[124],"accuracy":[125],"proposed":[128,148],"99.3%":[131],"98.7%":[133],"on":[134],"two":[135],"data":[137],"sets,":[138],"respectively.":[139],"Meanwhile,":[140],"experimental":[141],"results":[142],"demonstrate":[143],"effectiveness":[145],"in":[150],"identifying":[151],"both":[152],"categories":[154],"locations":[157],"components,":[160],"whose":[161],"superiority":[162],"has":[163],"been":[164],"verified":[165],"comprehensive":[168],"comparison":[169],"analysis":[170],"traditional":[172],"deep":[173],"learning":[174],"methods":[175],"state-of-art":[177],"methods,":[178],"including":[179],"residual-squeeze":[180],"net,":[181],"recurrent":[183],"network,":[185],"DenseNet.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":38},{"year":2022,"cited_by_count":25},{"year":2021,"cited_by_count":11}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
