{"id":"https://openalex.org/W6963350555","doi":"https://doi.org/10.21227/9m3c-xs98","title":"Vibration signal of high speed EMU air compressor","display_name":"Vibration signal of high speed EMU air compressor","publication_year":2024,"publication_date":"2024-04-30","ids":{"openalex":"https://openalex.org/W6963350555","doi":"https://doi.org/10.21227/9m3c-xs98"},"language":"en","primary_location":{"id":"doi:10.21227/9m3c-xs98","is_oa":true,"landing_page_url":"https://doi.org/10.21227/9m3c-xs98","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.21227/9m3c-xs98","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"PENG, LIQIANG","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"PENG, LIQIANG","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"GUO, KANG","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"GUO, KANG","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"ZHANG, SHUZHAO","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"ZHANG, SHUZHAO","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.8206999897956848},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6093000173568726},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.6010000109672546},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5983999967575073},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5525000095367432},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5372999906539917},{"id":"https://openalex.org/keywords/air-compressor","display_name":"Air compressor","score":0.5368000268936157},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5338000059127808},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5127999782562256},{"id":"https://openalex.org/keywords/gas-compressor","display_name":"Gas compressor","score":0.5123999714851379}],"concepts":[{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.8206999897956848},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6093000173568726},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.6010000109672546},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5983999967575073},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5525000095367432},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5372999906539917},{"id":"https://openalex.org/C2779983431","wikidata":"https://www.wikidata.org/wiki/Q978234","display_name":"Air compressor","level":2,"score":0.5368000268936157},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5338000059127808},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5127999782562256},{"id":"https://openalex.org/C131097465","wikidata":"https://www.wikidata.org/wiki/Q178898","display_name":"Gas compressor","level":2,"score":0.5123999714851379},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.499099999666214},{"id":"https://openalex.org/C198394728","wikidata":"https://www.wikidata.org/wiki/Q3695508","display_name":"Vibration","level":2,"score":0.4837999939918518},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4790000021457672},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.42890000343322754},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.415800005197525},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4097999930381775},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.38940000534057617},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.3582000136375427},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3571000099182129},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3538999855518341},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.353300005197525},{"id":"https://openalex.org/C2779855323","wikidata":"https://www.wikidata.org/wiki/Q1172774","display_name":"Daubechies wavelet","level":5,"score":0.3517000079154968},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.33820000290870667},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.33379998803138733},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.32359999418258667},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.31150001287460327},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2712000012397766},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.26910001039505005},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C200398353","wikidata":"https://www.wikidata.org/wiki/Q63973","display_name":"Turbomachinery","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C2778626561","wikidata":"https://www.wikidata.org/wiki/Q6086067","display_name":"Isomap","level":4,"score":0.25859999656677246},{"id":"https://openalex.org/C14948415","wikidata":"https://www.wikidata.org/wiki/Q7310972","display_name":"Relevance vector machine","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21227/9m3c-xs98","is_oa":true,"landing_page_url":"https://doi.org/10.21227/9m3c-xs98","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"dataset"}],"best_oa_location":{"id":"doi:10.21227/9m3c-xs98","is_oa":true,"landing_page_url":"https://doi.org/10.21227/9m3c-xs98","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dataset"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"&nbsp;The":[0],"timely":[1],"and":[2,51,64,95,139,150,170,180,189,209,220],"accurate":[3],"diagnosis":[4,38,131,202,226],"of":[5,62,73,89,187,194,198,222],"severe":[6],"faults":[7],"in":[8,76,176],"the":[9,18,59,71,87,90,99,137,145,152,160,199,218],"high-speed":[10,33],"train":[11,34],"air":[12,35,100,223],"compressor":[13,36,101,224],"is":[14,67,116],"crucial":[15],"due":[16],"to":[17,26,69,104,159,178],"potential":[19],"for":[20,118,217],"significant":[21],"safety":[22],"issues.":[23],"In":[24],"response":[25],"this":[27,29],"problem,":[28],"paper":[30],"proposes":[31],"a":[32,183,190],"fault":[37,130,201,225],"method":[39,143],"based":[40],"on":[41],"an&nbsp;improved":[42],"complete":[43],"ensemble":[44],"empirical":[45],"mode":[46],"decomposition":[47],"adaptive":[48],"noise":[49],"(ICEEMDAN)":[50],"t-Distributed":[52],"Stochastic":[53],"Neighbor":[54],"Embedding":[55],"(t-SNE)":[56],"algorithm.":[57],"Firstly,":[58],"joint":[60],"denoising":[61,84,142,173],"ICEEMDAN":[63,138],"wavelet":[65,140,171],"thresholding":[66,141,172],"employed":[68],"address":[70],"issue":[72],"unrealistic":[74],"components":[75],"traditional":[77],"CEEMDAN":[78],"signal":[79],"decomposition.":[80],"This":[81],"approach":[82],"ensures":[83],"while":[85],"preserving":[86],"integrity":[88],"original":[91],"signal.":[92],"Finally,":[93],"vibration":[94],"pressure":[96],"signals":[97],"from":[98],"are":[102],"subjected":[103],"feature":[105,109,120],"extraction,":[106,121],"constructing":[107],"high-dimensional":[108],"vectors.":[110],"The":[111,196],"t-SNE":[112],"manifold":[113],"learning":[114],"algorithm":[115],"applied":[117],"secondary":[119],"creating":[122],"an":[123],"MPGA-SVM":[124,200],"(Multi-Objective":[125],"Genetic":[126],"Algorithm-Support":[127],"Vector":[128],"Machine)":[129],"model.":[132],"Experimental":[133],"results":[134],"demonstrate":[135],"that":[136],"improves":[144],"signal-to-noise":[146],"ratio":[147],"by":[148,156],"6.5%":[149],"reduces":[151],"mean":[153],"square":[154],"error":[155],"16.1%":[157],"compared":[158],"Complete":[161],"Ensemble":[162],"Empirical":[163],"Mode":[164],"Decomposition":[165],"with":[166],"Adaptive":[167],"Noise":[168],"(CEEMDAN)":[169],"method.":[174],"t-SNE,":[175],"comparison":[177],"ISOMAP":[179],"LLE,":[181],"produces":[182],"minimum":[184],"intra-class":[185],"distance":[186,193],"1.28":[188],"maximum":[191],"inter-class":[192],"43.1.":[195],"accuracy":[197],"model":[203],"reaches":[204],"98.33%,":[205],"confirming":[206],"its":[207],"effectiveness":[208],"reliability.":[210],"These":[211],"studies":[212],"provide":[213],"important":[214],"theoretical":[215],"support":[216],"improvement":[219],"application":[221],"methods.":[227]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}
