{"id":"https://openalex.org/W2551047957","doi":"https://doi.org/10.1109/urai.2016.7734071","title":"Automaton fault diagnosis method of multi-parameters integration for feature extraction","display_name":"Automaton fault diagnosis method of multi-parameters integration for feature extraction","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2551047957","doi":"https://doi.org/10.1109/urai.2016.7734071","mag":"2551047957"},"language":"en","primary_location":{"id":"doi:10.1109/urai.2016.7734071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/urai.2016.7734071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)","raw_type":"proceedings-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/A5009845865","display_name":"Mingzhi Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095683","display_name":"Jinzhong University","ror":"https://ror.org/007ywhm20","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210095683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingzhi Pan","raw_affiliation_strings":["School of Mechanical Engineering, Jinzhong University, Shanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Jinzhong University, Shanxi, China","institution_ids":["https://openalex.org/I4210095683"]}]},{"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":false,"raw_author_name":"Hongxia Pan","raw_affiliation_strings":["School of Mechanical and Power Engineering, North University of China, Taiyuan, Shanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical and Power Engineering, North University of China, Taiyuan, Shanxi, China","institution_ids":["https://openalex.org/I135714990"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058602237","display_name":"Xin Xu","orcid":"https://orcid.org/0000-0001-9211-6606"},"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":"Xu Xin","raw_affiliation_strings":["School of Mechanical and Power Engineering, North University of China, Taiyuan, Shanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical and Power Engineering, North University of China, Taiyuan, Shanxi, China","institution_ids":["https://openalex.org/I135714990"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11992061,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":null,"first_page":"411","last_page":"416"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.8277000188827515,"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"}},"topics":[{"id":"https://openalex.org/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.8277000188827515,"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"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.7615000009536743,"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/feature-extraction","display_name":"Feature extraction","score":0.5757606029510498},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5568856000900269},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5548210144042969},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5503222942352295},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4888748526573181},{"id":"https://openalex.org/keywords/fractal-dimension","display_name":"Fractal dimension","score":0.4860385060310364},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4474218487739563},{"id":"https://openalex.org/keywords/correlation-dimension","display_name":"Correlation dimension","score":0.4348601698875427},{"id":"https://openalex.org/keywords/vibration","display_name":"Vibration","score":0.42087316513061523},{"id":"https://openalex.org/keywords/fractal","display_name":"Fractal","score":0.4171305000782013},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38982391357421875},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3736325204372406},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26200878620147705},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.12283316254615784}],"concepts":[{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5757606029510498},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5568856000900269},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5548210144042969},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5503222942352295},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4888748526573181},{"id":"https://openalex.org/C26546657","wikidata":"https://www.wikidata.org/wiki/Q1412452","display_name":"Fractal dimension","level":3,"score":0.4860385060310364},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4474218487739563},{"id":"https://openalex.org/C110601934","wikidata":"https://www.wikidata.org/wiki/Q5172849","display_name":"Correlation dimension","level":4,"score":0.4348601698875427},{"id":"https://openalex.org/C198394728","wikidata":"https://www.wikidata.org/wiki/Q3695508","display_name":"Vibration","level":2,"score":0.42087316513061523},{"id":"https://openalex.org/C40636538","wikidata":"https://www.wikidata.org/wiki/Q81392","display_name":"Fractal","level":2,"score":0.4171305000782013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38982391357421875},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3736325204372406},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26200878620147705},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.12283316254615784},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/urai.2016.7734071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/urai.2016.7734071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2029903936","https://openalex.org/W2367636979","https://openalex.org/W7058246850","https://openalex.org/W7065770958"],"related_works":["https://openalex.org/W2394117909","https://openalex.org/W2896054214","https://openalex.org/W2355197944","https://openalex.org/W2017118246","https://openalex.org/W2354661593","https://openalex.org/W2382240109","https://openalex.org/W2368475191","https://openalex.org/W2391311021","https://openalex.org/W2389188284","https://openalex.org/W2026209355"],"abstract_inverted_index":{"High-speed":[0],"automaton":[1,74,126,211,263],"is":[2,58,153,164,188,237,403],"core":[3],"component":[4,21,152],"of":[5,10,19,31,45,52,150,225,232,241,272,302,315,323,327,386,399,410,414,434,443,450,466,491],"small":[6],"caliber":[7],"artillery,":[8],"because":[9],"its":[11,23,104],"poor":[12],"working":[13,24],"condition,":[14],"the":[15,29,43,95,98,125,134,148,156,168,171,185,192,200,223,242,252,257,273,281,289,295,304,312,324,349,383,396,411,425,431,447,456,464],"crack":[16],"and":[17,22,34,54,70,80,103,130,143,198,308,320,416,460,472],"wear":[18],"each":[20],"reliability":[25],"have":[26],"gradually":[27],"become":[28],"focus":[30],"fault":[32,117,151,213,243,334,358,441,457,467,479,489],"monitoring":[33],"diagnosis.":[35],"This":[36,482],"traditional":[37],"test":[38,69],"method":[39,72,163,187],"(mainly":[40],"used":[41,165,189],"in":[42,266,294,342,388],"field":[44],"weapon)":[46],"not":[47],"only":[48],"needs":[49],"a":[50,485],"lot":[51],"cost":[53],"time,":[55,109],"but":[56],"also":[57],"vulnerable":[59],"to":[60,85,89,93,115,119,124,139,147,166,179,190,276,280,332,347,354,361,381,405,423,446,477],"many":[61],"uncertain":[62],"factors.":[63],"Therefore,":[64],"this":[65],"paper":[66,483],"uses":[67],"modern":[68],"analysis":[71,157],"collecting":[73],"vibration":[75,106,144,193,274],"signal":[76,82,136,145,182,194,387],"during":[77],"shooting":[78],"action":[79],"applying":[81],"processing":[83],"methods":[84],"extract":[86,478],"features":[87,380],"susceptible":[88],"fault,":[90],"so":[91],"as":[92,155,212,378],"identify":[94,333,362,406,440],"fault.":[96],"Considering":[97],"high-speed":[99],"automatic":[100],"movement":[101,127],"process":[102],"nonlinear":[105],"signal,":[107,169],"short":[108],"transient,":[110],"impact":[111,174],"properties.":[112],"In":[113,177,239,270,345],"order":[114,178,346],"make":[116],"information":[118,207,227,473],"be":[120,277],"highlighted,":[121],"firstly,":[122],"according":[123,279],"patterns":[128],"decomposition":[129],"time":[131,389],"cycle":[132],"diagram,":[133],"time-domain":[135],"peak":[137],"corresponds":[138],"collision":[140],"between":[141,303],"parts,":[142],"corresponding":[146,290],"motion":[149],"intercepted":[154],"object.":[158],"Then,":[159],"wavelet":[160],"threshold":[161],"de-noising":[162],"preprocess":[167],"making":[170],"open":[172],"atresia":[173],"obviously.":[175],"Secondly,":[176],"comprehensively":[180],"measure":[181],"fractal":[183,196,202],"characteristics,":[184],"override":[186],"calculate":[191,299],"generalized":[195,201],"dimension":[197,203,210],"draw":[199,321],"spectrum,":[204],"box":[205],"dimension,":[206,208],"correlation":[209],"feature":[214,226,244],"values":[215],"are":[216,340,352,376,420,475],"extracted.":[217],"Then":[218],"quantitative":[219,379],"diagnosis":[220,490],"index":[221,230,292,306,313,325,397,412,432,448],"at":[222],"level":[224],"integration":[228],"--the":[229],"distance":[231,314,326,398,413,433,449],"three":[233,267,316,328],"demensional":[234,317,329],"characteristic":[235,284,291,305,318,330,359,401,418,436,452,458,480],"parameters":[236,245,331,360,402,419,437,459],"proposed.":[238],"view":[240,271],"extracted":[246,377],"under":[247],"various":[248],"conditions,":[249],"We":[250],"compute":[251],"average":[253],"respectively,":[254],"then":[255],"obtain":[256],"four":[258,264,309],"standard":[259,310],"centers":[260],"separately":[261],"representing":[262],"conditions":[265,335,442],"dimensional":[268],"space.":[269],"signals":[275],"detected,":[278],"extracting":[282],"three-dimensional":[283,296,417,451],"parameters,":[285,319],"we":[286,351],"can":[287,438,462],"find":[288],"points":[293,307],"space,":[297],"respectively":[298],"these":[300],"distances":[301],"centers,":[311],"graphs":[322,409],"intuitively.":[336],"Some":[337],"identification":[338],"errors":[339],"found":[341],"certain":[343],"condition.":[344],"improve":[348,463],"deficiencies,":[350],"determined":[353],"increase":[355,357,424],"dimensions,":[356],"conditions.":[363,407],"So,":[364,454],"singular":[365],"spectrum":[366,369],"entropy,":[367,370],"power":[368],"local":[371],"wave":[372],"spatial":[373],"spectral":[374],"entropy":[375,474],"describe":[382],"state":[384],"changes":[385],"domain,":[390,392],"frequency":[391],"time-frequency":[393],"domain.":[394],"Calculating":[395],"six-demensional":[400],"suggested":[404],"Two":[408],"six-dimensional":[415,435],"drawed":[421],"simultaneously":[422],"comparative.":[426],"Diagnosis":[427],"results":[428],"indicate":[429],"that:":[430],"accuratly":[439],"automaton,":[444],"compared":[445],"parameters.":[453],"increasing":[455],"dimensions":[461],"accuracy":[465],"identification.":[468],"Also,":[469],"multi-fractal":[470],"theory":[471],"sensitive":[476],"values.":[481],"provides":[484],"new":[486],"idea":[487],"for":[488],"automaton.":[492]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}