{"id":"https://openalex.org/W2589746145","doi":"https://doi.org/10.3390/e19030086","title":"Motion Sequence Decomposition-Based Hybrid Entropy Feature and Its Application to Fault Diagnosis of a High-Speed Automatic Mechanism","display_name":"Motion Sequence Decomposition-Based Hybrid Entropy Feature and Its Application to Fault Diagnosis of a High-Speed Automatic Mechanism","publication_year":2017,"publication_date":"2017-02-24","ids":{"openalex":"https://openalex.org/W2589746145","doi":"https://doi.org/10.3390/e19030086","mag":"2589746145"},"language":"en","primary_location":{"id":"doi:10.3390/e19030086","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e19030086","pdf_url":"https://www.mdpi.com/1099-4300/19/3/86/pdf?version=1487932518","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/19/3/86/pdf?version=1487932518","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101781010","display_name":"Baoxiang Wang","orcid":"https://orcid.org/0000-0002-6569-9049"},"institutions":[{"id":"https://openalex.org/I135714990","display_name":"North University of China","ror":"https://ror.org/047bp1713","country_code":"CN","type":"education","lineage":["https://openalex.org/I135714990"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baoxiang Wang","raw_affiliation_strings":["School of Mechanical and Power Engineering, North University of China, Taiyuan 030051, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical and Power Engineering, North University of China, Taiyuan 030051, China","institution_ids":["https://openalex.org/I135714990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026062458","display_name":"Pan Hong-xia","orcid":null},"institutions":[{"id":"https://openalex.org/I135714990","display_name":"North University of China","ror":"https://ror.org/047bp1713","country_code":"CN","type":"education","lineage":["https://openalex.org/I135714990"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongxia Pan","raw_affiliation_strings":["School of Mechanical and Power Engineering, North University of China, Taiyuan 030051, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical and Power Engineering, North University of China, Taiyuan 030051, China","institution_ids":["https://openalex.org/I135714990"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014945614","display_name":"Heng Du","orcid":"https://orcid.org/0000-0002-2661-5818"},"institutions":[{"id":"https://openalex.org/I135714990","display_name":"North University of China","ror":"https://ror.org/047bp1713","country_code":"CN","type":"education","lineage":["https://openalex.org/I135714990"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng Du","raw_affiliation_strings":["School of Mechanical and Power Engineering, North University of China, Taiyuan 030051, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical and Power Engineering, North University of China, Taiyuan 030051, China","institution_ids":["https://openalex.org/I135714990"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5026062458"],"corresponding_institution_ids":["https://openalex.org/I135714990"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.204,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.48836402,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"19","issue":"3","first_page":"86","last_page":"86"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9984999895095825,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9984999895095825,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9962000250816345,"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":0.9690999984741211,"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/computer-science","display_name":"Computer science","score":0.7303661108016968},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.6470450162887573},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5055069923400879},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.4881783127784729},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.48437580466270447},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4679226875305176},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4674186408519745},{"id":"https://openalex.org/keywords/automaton","display_name":"Automaton","score":0.4614623188972473},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.44950568675994873},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42823269963264465},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4252944886684418},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4168659746646881},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.40563106536865234},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.2454824447631836},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08328831195831299}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7303661108016968},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.6470450162887573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5055069923400879},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.4881783127784729},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.48437580466270447},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4679226875305176},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4674186408519745},{"id":"https://openalex.org/C112505250","wikidata":"https://www.wikidata.org/wiki/Q787116","display_name":"Automaton","level":2,"score":0.4614623188972473},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.44950568675994873},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42823269963264465},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4252944886684418},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4168659746646881},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.40563106536865234},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.2454824447631836},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08328831195831299},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/e19030086","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e19030086","pdf_url":"https://www.mdpi.com/1099-4300/19/3/86/pdf?version=1487932518","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d3f9a6a22a4b413ba1eeffcd95b7e481","is_oa":true,"landing_page_url":"https://doaj.org/article/d3f9a6a22a4b413ba1eeffcd95b7e481","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 19, Iss 3, p 86 (2017)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/19/3/86/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e19030086","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy; Volume 19; Issue 3; Pages: 86","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e19030086","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e19030086","pdf_url":"https://www.mdpi.com/1099-4300/19/3/86/pdf?version=1487932518","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8100000023841858,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G1077903415","display_name":null,"funder_award_id":"(Grant No. 51175480)","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3784825443","display_name":null,"funder_award_id":"51175480","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":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2589746145.pdf","grobid_xml":"https://content.openalex.org/works/W2589746145.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W427289305","https://openalex.org/W1889820893","https://openalex.org/W1971219721","https://openalex.org/W1975687401","https://openalex.org/W1978670814","https://openalex.org/W1987688897","https://openalex.org/W1991941961","https://openalex.org/W1996548840","https://openalex.org/W2027872902","https://openalex.org/W2030276507","https://openalex.org/W2034115912","https://openalex.org/W2061438946","https://openalex.org/W2078994304","https://openalex.org/W2087273325","https://openalex.org/W2094625209","https://openalex.org/W2153635508","https://openalex.org/W2170614103","https://openalex.org/W2189002369","https://openalex.org/W2189028327","https://openalex.org/W2203044710","https://openalex.org/W2219903032","https://openalex.org/W2294429651","https://openalex.org/W2305066525","https://openalex.org/W2320286509","https://openalex.org/W2346585872","https://openalex.org/W2514763704","https://openalex.org/W2516154524","https://openalex.org/W2558217427"],"related_works":["https://openalex.org/W3014107421","https://openalex.org/W2363056446","https://openalex.org/W2081563414","https://openalex.org/W2359718298","https://openalex.org/W2377062149","https://openalex.org/W2380939102","https://openalex.org/W154554909","https://openalex.org/W2072581623","https://openalex.org/W2011248322","https://openalex.org/W2329112433"],"abstract_inverted_index":{"High-speed":[0],"automatic":[1,90,125],"weapons":[2],"play":[3],"an":[4,107,231],"important":[5],"role":[6],"in":[7,36,85,113,266,282],"the":[8,27,62,69,86,119,124,129,141,157,167,172,176,186,195,216,235,238,256,263,286,298,303],"field":[9],"of":[10,19,52,55,68,89,123,133,150,175,191,215,237,255,274],"national":[11],"defense.":[12],"However,":[13],"current":[14],"research":[15],"on":[16,23,185],"reliability":[17],"analysis":[18],"automaton":[20,45,70,217,277],"principally":[21],"relies":[22],"simulations":[24],"due":[25],"to":[26,34,47,59,81,105,110,153,171,211,233,249,290],"fact":[28],"that":[29,262],"experimental":[30],"data":[31,252],"are":[32,200,209],"difficult":[33],"collect":[35,250],"real":[37,283],"life.":[38],"Different":[39],"from":[40,140,166],"rotating":[41],"machinery,":[42],"a":[43,53,95,148,161,275,292],"high-speed":[44,114,276],"needs":[46],"accomplish":[48],"complex":[49],"motion":[50,96],"consisting":[51],"series":[54],"impacts.":[56],"In":[57],"addition":[58],"strong":[60],"noise,":[61],"impacts":[63,151,169],"generated":[64,159],"by":[65,160],"different":[66],"components":[67,196],"will":[71],"interfere":[72],"with":[73,83,197,297],"each":[74],"other.":[75],"There":[76],"is":[77,144,164,182,228,269,288],"no":[78],"effective":[79,108,270],"approach":[80,99,109],"cope":[82],"this":[84,267],"fault":[87,111,272],"diagnosis":[88,273,294],"mechanisms.":[91],"This":[92],"paper":[93,268],"proposes":[94],"sequence":[97],"decomposition":[98,180,221],"combining":[100],"modern":[101],"signal":[102,138],"processing":[103],"techniques":[104],"develop":[106],"detection":[112],"automatons.":[115],"We":[116,244],"first":[117,183],"investigate":[118],"entire":[120],"working":[121],"procedure":[122],"mechanism":[126],"and":[127,194,278,302],"calculate":[128],"corresponding":[130,152],"action":[131,154,173],"times":[132],"travel":[134],"involved.":[135],"The":[136],"vibration":[137,251],"collected":[139],"shooting":[142,247],"experiment":[143],"then":[145],"divided":[146],"into":[147],"number":[149],"orders.":[155],"Only":[156],"segment":[158],"faulty":[162],"component":[163],"isolated":[165],"original":[168],"according":[170],"time":[174],"component.":[177],"Wavelet":[178],"packet":[179],"(WPD)":[181],"applied":[184,281],"resulting":[187],"signals":[188],"for":[189,202,253,271],"investigation":[190],"energy":[192,199],"distribution,":[193],"higher":[198],"selected":[201],"feature":[203],"extraction.":[204],"Three":[205],"information":[206],"entropy":[207],"features":[208],"utilized":[210],"distinguish":[212],"various":[213],"states":[214],"using":[218],"empirical":[219],"mode":[220],"(EMD).":[222],"A":[223],"gray-wolf":[224],"optimization":[225,306],"(GWO)":[226],"algorithm":[227,300],"introduced":[229],"as":[230],"alternative":[232],"improve":[234],"performance":[236],"support":[239],"vector":[240],"machine":[241],"(SVM)":[242],"classifier.":[243],"carry":[245],"out":[246],"experiments":[248],"demonstration":[254],"proposed":[257,264],"work.":[258],"Experimental":[259],"results":[260],"show":[261],"work":[265],"can":[279],"be":[280],"applications.":[284],"Moreover,":[285],"GWO":[287],"able":[289],"provide":[291],"competitive":[293],"result":[295],"compared":[296],"genetic":[299],"(GA)":[301],"particle":[304],"swarm":[305],"(PSO)":[307],"algorithm.":[308]},"counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
