{"id":"https://openalex.org/W3118779207","doi":"https://doi.org/10.1109/access.2021.3049159","title":"Use AF-CNN for End-to-End Fiber Vibration Signal Recognition","display_name":"Use AF-CNN for End-to-End Fiber Vibration Signal Recognition","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3118779207","doi":"https://doi.org/10.1109/access.2021.3049159","mag":"3118779207"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3049159","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3049159","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09314145.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09314145.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038564325","display_name":"Saisai Ruan","orcid":"https://orcid.org/0000-0003-4444-9312"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Saisai Ruan","raw_affiliation_strings":["Key Laboratory of Signal Detection and Processing, College of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi, China"],"raw_orcid":"https://orcid.org/0000-0003-4444-9312","affiliations":[{"raw_affiliation_string":"Key Laboratory of Signal Detection and Processing, College of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004913357","display_name":"Jiaqing Mo","orcid":"https://orcid.org/0000-0001-8607-1966"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqing Mo","raw_affiliation_strings":["Key Laboratory of Signal Detection and Processing, College of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Signal Detection and Processing, College of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100741491","display_name":"Liang Xu","orcid":"https://orcid.org/0000-0003-0059-426X"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Xu","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Tianjin University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-0059-426X","affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Tianjin University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054814122","display_name":"Gang Zhou","orcid":"https://orcid.org/0000-0002-4425-9837"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Zhou","raw_affiliation_strings":["Key Laboratory of Signal Detection and Processing, College of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Signal Detection and Processing, College of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100349259","display_name":"Yajun Liu","orcid":"https://orcid.org/0000-0002-8203-5762"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yajun Liu","raw_affiliation_strings":["Key Laboratory of Signal Detection and Processing, College of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Signal Detection and Processing, College of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100327327","display_name":"Xin Zhang","orcid":"https://orcid.org/0000-0001-5647-2777"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Zhang","raw_affiliation_strings":["Key Laboratory of Signal Detection and Processing, College of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Signal Detection and Processing, College of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi, China","institution_ids":["https://openalex.org/I96908189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5038564325"],"corresponding_institution_ids":["https://openalex.org/I96908189"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.0169,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.74939355,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"9","issue":null,"first_page":"6713","last_page":"6720"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10205","display_name":"Advanced Fiber Optic Sensors","score":0.9980999827384949,"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/T10205","display_name":"Advanced Fiber Optic Sensors","score":0.9980999827384949,"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/T10988","display_name":"Advanced Fiber Laser Technologies","score":0.9634000062942505,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.954200029373169,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8092068433761597},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7282633185386658},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7245677709579468},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.709652841091156},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6531973481178284},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.58628249168396},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5034438967704773},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.502310037612915},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.46823257207870483},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4611284136772156},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4318726658821106},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09026497602462769}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8092068433761597},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7282633185386658},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7245677709579468},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.709652841091156},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6531973481178284},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.58628249168396},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5034438967704773},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.502310037612915},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.46823257207870483},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4611284136772156},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4318726658821106},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09026497602462769},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3049159","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3049159","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09314145.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f6d1c8748d0e4f468b53954c47d42f68","is_oa":true,"landing_page_url":"https://doaj.org/article/f6d1c8748d0e4f468b53954c47d42f68","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":"IEEE Access, Vol 9, Pp 6713-6720 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3049159","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3049159","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09314145.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320328898","display_name":"Natural Science Foundation of Xinjiang","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3118779207.pdf","grobid_xml":"https://content.openalex.org/works/W3118779207.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1604034532","https://openalex.org/W1972019841","https://openalex.org/W1972059487","https://openalex.org/W1972656492","https://openalex.org/W1998594022","https://openalex.org/W2072536821","https://openalex.org/W2097988347","https://openalex.org/W2194775991","https://openalex.org/W2292944251","https://openalex.org/W2326927858","https://openalex.org/W2382299106","https://openalex.org/W2526050071","https://openalex.org/W2566781703","https://openalex.org/W2587165555","https://openalex.org/W2611158135","https://openalex.org/W2757227051","https://openalex.org/W2770454110","https://openalex.org/W2777746061","https://openalex.org/W2882975048","https://openalex.org/W2901526063","https://openalex.org/W2964052309","https://openalex.org/W2988177884","https://openalex.org/W4241166586","https://openalex.org/W6643235425","https://openalex.org/W6727253422","https://openalex.org/W6756221392"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2082756648","https://openalex.org/W2964954556","https://openalex.org/W3034421924","https://openalex.org/W2982536526","https://openalex.org/W4386858688","https://openalex.org/W4380302312","https://openalex.org/W4390971171","https://openalex.org/W4385338604","https://openalex.org/W3081626085"],"abstract_inverted_index":{"Traditional":[0],"optical":[1],"fiber":[2],"vibration":[3],"signal":[4,10,135,158],"(OFVS)":[5],"recognition":[6,61,179,193],"research":[7],"focuses":[8],"on":[9,30,123],"endpoint":[11],"detection":[12],"and":[13,34,47,65,68,181,201,210],"feature":[14,66],"extraction.":[15],"These":[16],"two":[17],"aspects":[18],"directly":[19,89],"determine":[20],"the":[21,40,52,58,69,91,95,99,103,106,113,124,133,156,172,184],"success":[22],"of":[23,71,98,142],"OFVS":[24,60,206],"recognition.":[25],"The":[26,127,195],"traditional":[27,59,177,191],"method":[28],"relies":[29],"artificially":[31],"designed":[32],"features":[33],"has":[35],"a":[36,119,148,161],"strong":[37],"pertinence":[38],"to":[39,51,77,111,138,154],"classification":[41,92],"target,":[42],"resulting":[43],"in":[44],"poor":[45],"stability":[46],"flexibility.":[48],"In":[49,101],"response":[50],"above":[53],"problems,":[54],"this":[55],"paper":[56,170],"combines":[57],"ideas":[62],"(time-frequency":[63],"analysis":[64],"extraction)":[67],"characteristics":[70],"deep":[72],"learning":[73,75],"automatic":[74],"parameters":[76],"construct":[78],"an":[79],"end-to-end":[80],"adaptive":[81],"filtering":[82,137],"convolutional":[83,150],"neural":[84,151],"network":[85,114,152,174],"(AF-CNN),":[86],"which":[87],"can":[88,130,198,203],"get":[90],"results":[93],"through":[94],"iterative":[96],"update":[97],"network.":[100],"modeling":[102],"original":[104,125,134],"signal,":[105],"following":[107],"steps":[108],"were":[109],"taken":[110],"make":[112],"interpretable.":[115],"First,":[116],"we":[117],"use":[118],"one-dimensional":[120],"(1-D)":[121],"convolution":[122,128],"OFVS.":[126],"kernel":[129],"adaptively":[131],"treat":[132],"perform":[136],"obtain":[139],"filtered":[140,157],"signals":[141],"different":[143],"frequency":[144],"bands.":[145],"Second,":[146],"using":[147],"general":[149],"(CNN)":[153],"extract":[155],"features.":[159],"Finally,":[160],"multi-layer":[162],"perceptron":[163],"(MLP)":[164],"is":[165,188],"used":[166],"for":[167],"classification.":[168],"This":[169],"compares":[171],"AF-CNN":[173,185],"with":[175,207],"three":[176],"pattern":[178,192],"methods":[180],"proves":[182],"that":[183],"network's":[186],"accuracy":[187,197],"better":[189],"than":[190],"methods.":[194],"average":[196],"reach":[199],"96.7%,":[200],"it":[202],"effectively":[204],"distinguish":[205],"weaker":[208],"energy":[209],"similar":[211],"waveforms.":[212]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
