{"id":"https://openalex.org/W2959675909","doi":"https://doi.org/10.1109/tvt.2019.2925903","title":"Fault Diagnosis of Train Plug Door Based on a Hybrid Criterion for IMFs Selection and Fractional Wavelet Package Energy Entropy","display_name":"Fault Diagnosis of Train Plug Door Based on a Hybrid Criterion for IMFs Selection and Fractional Wavelet Package Energy Entropy","publication_year":2019,"publication_date":"2019-07-12","ids":{"openalex":"https://openalex.org/W2959675909","doi":"https://doi.org/10.1109/tvt.2019.2925903","mag":"2959675909"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2019.2925903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2019.2925903","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","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/A5015347934","display_name":"Yuan Cao","orcid":"https://orcid.org/0000-0001-6631-4908"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuan Cao","raw_affiliation_strings":["National Engineering Research Center of Rail Transportation Operation and Control System, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6631-4908","affiliations":[{"raw_affiliation_string":"National Engineering Research Center of Rail Transportation Operation and Control System, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014206402","display_name":"Yongkui Sun","orcid":"https://orcid.org/0000-0001-6582-1342"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongkui Sun","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6582-1342","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000799818","display_name":"Guo Xie","orcid":"https://orcid.org/0000-0002-9948-453X"},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guo Xie","raw_affiliation_strings":["Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi\u2019an University of Technology, Xi\u2019an, China","Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi'an University of Technology, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-9948-453X","affiliations":[{"raw_affiliation_string":"Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi\u2019an University of Technology, Xi\u2019an, China","institution_ids":["https://openalex.org/I4210131919"]},{"raw_affiliation_string":"Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi'an University of Technology, Xi'an, China","institution_ids":["https://openalex.org/I4210131919"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101749804","display_name":"Tao Wen","orcid":"https://orcid.org/0000-0002-8253-9338"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Wen","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5015347934"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":21.5634,"has_fulltext":false,"cited_by_count":221,"citation_normalized_percentile":{"value":0.99700939,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"68","issue":"8","first_page":"7544","last_page":"7551"},"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/T10842","display_name":"Railway Engineering and Dynamics","score":0.9639999866485596,"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/T11343","display_name":"Power Transformer Diagnostics and Insulation","score":0.95169997215271,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.8012464046478271},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.6364281177520752},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6118218898773193},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5726191401481628},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45091256499290466},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45069628953933716},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4411580562591553},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.4280169606208801},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.370791494846344},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.3636305630207062},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.35020607709884644},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2268165647983551}],"concepts":[{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.8012464046478271},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.6364281177520752},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6118218898773193},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5726191401481628},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45091256499290466},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45069628953933716},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4411580562591553},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.4280169606208801},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.370791494846344},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3636305630207062},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.35020607709884644},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2268165647983551},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2019.2925903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2019.2925903","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8999999761581421,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G2787828080","display_name":null,"funder_award_id":"U1734211","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3949384069","display_name":null,"funder_award_id":"61873201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7221012831","display_name":null,"funder_award_id":"U1534208","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W351966126","https://openalex.org/W1217003803","https://openalex.org/W1988725338","https://openalex.org/W1988743659","https://openalex.org/W2000646906","https://openalex.org/W2004884583","https://openalex.org/W2007221293","https://openalex.org/W2031638733","https://openalex.org/W2070779870","https://openalex.org/W2079025339","https://openalex.org/W2108663617","https://openalex.org/W2171309390","https://openalex.org/W2225563181","https://openalex.org/W2378851280","https://openalex.org/W2392674060","https://openalex.org/W2415210186","https://openalex.org/W2423195739","https://openalex.org/W2482102801","https://openalex.org/W2504295827","https://openalex.org/W2568828645","https://openalex.org/W2588926225","https://openalex.org/W2756026007","https://openalex.org/W2770767853","https://openalex.org/W2783137155","https://openalex.org/W2807874407","https://openalex.org/W2812001514","https://openalex.org/W2912406262","https://openalex.org/W2913674227","https://openalex.org/W2958727589","https://openalex.org/W3007232733","https://openalex.org/W6647567023","https://openalex.org/W7036228833"],"related_works":["https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904","https://openalex.org/W2390914021","https://openalex.org/W2389417819"],"abstract_inverted_index":{"The":[0,64,137],"train":[1,18,35],"plug":[2,36],"door":[3],"is":[4,38,62,91,98,112,124],"the":[5,22,72,76,108,130,141],"only":[6],"way":[7],"for":[8,34,100],"passengers":[9],"getting":[10],"on":[11,41,50],"and":[12,54,102,150],"off.":[13],"Its":[14],"failures":[15],"will":[16],"make":[17],"operation":[19],"ineffective.":[20],"Taking":[21],"developed":[23],"digital":[24],"signal":[25],"processing":[26],"technologies":[27],"into":[28],"consideration,":[29],"a":[30,45],"data-driven":[31],"diagnosis":[32],"method":[33,48,111,143],"doors":[37],"proposed":[39,109,142],"based":[40,49],"sound":[42],"recognition.":[43],"First,":[44],"novel":[46,81],"preprocessing":[47,110],"empirical":[51],"mode":[52,57],"decomposition":[53,87,134],"hybrid":[55],"intrinsic":[56],"functions":[58],"(IMFs)":[59],"selection":[60],"criterion":[61],"proposed.":[63,92],"selected":[65],"significant":[66],"IMFs":[67],"are":[68],"used":[69,99],"to":[70,116],"reconstruct":[71],"signals.":[73],"Inspired":[74],"by":[75],"idea":[77],"of":[78,113],"fractional":[79,84],"calculus,":[80],"entropy":[82,89],"named":[83],"wavelet":[85,132],"package":[86,133],"energy":[88,135],"(FWPDE)":[90],"Finally,":[93],"multi-class":[94],"support":[95],"vector":[96],"machine":[97],"classification":[101],"validation.":[103],"Experimental":[104],"results":[105],"indicate":[106],"that":[107],"great":[114],"significance":[115],"extract":[117],"effective":[118],"FWPDE":[119,123],"features.":[120],"In":[121],"addition,":[122],"more":[125],"powerful":[126],"in":[127],"comparison":[128],"with":[129],"classical":[131],"entropy.":[136],"identification":[138],"accuracy":[139],"using":[140],"reaches":[144],"96.28%,":[145],"which":[146],"demonstrates":[147],"its":[148],"effectiveness":[149],"superiority.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":30},{"year":2023,"cited_by_count":38},{"year":2022,"cited_by_count":31},{"year":2021,"cited_by_count":50},{"year":2020,"cited_by_count":35},{"year":2019,"cited_by_count":12}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
