{"id":"https://openalex.org/W4387702856","doi":"https://doi.org/10.3390/s23208513","title":"Real-Time Recognition Method for Key Signals of Rock Fracture Acoustic Emissions Based on Deep Learning","display_name":"Real-Time Recognition Method for Key Signals of Rock Fracture Acoustic Emissions Based on Deep Learning","publication_year":2023,"publication_date":"2023-10-17","ids":{"openalex":"https://openalex.org/W4387702856","doi":"https://doi.org/10.3390/s23208513","pmid":"https://pubmed.ncbi.nlm.nih.gov/37896608"},"language":"en","primary_location":{"id":"doi:10.3390/s23208513","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23208513","pdf_url":"https://www.mdpi.com/1424-8220/23/20/8513/pdf?version=1697529454","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/20/8513/pdf?version=1697529454","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057794118","display_name":"Lin Sun","orcid":"https://orcid.org/0000-0003-0429-4037"},"institutions":[{"id":"https://openalex.org/I137506752","display_name":"North China University of Science and Technology","ror":"https://ror.org/04z4wmb81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137506752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Sun","raw_affiliation_strings":["College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China","Hebei Green Intelligent Mining Technology Innovation Center, Tangshan 063210, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China","institution_ids":["https://openalex.org/I137506752"]},{"raw_affiliation_string":"Hebei Green Intelligent Mining Technology Innovation Center, Tangshan 063210, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lisen Lin","orcid":"https://orcid.org/0009-0004-2488-4768"},"institutions":[{"id":"https://openalex.org/I137506752","display_name":"North China University of Science and Technology","ror":"https://ror.org/04z4wmb81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137506752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lisen Lin","raw_affiliation_strings":["College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China","Hebei Green Intelligent Mining Technology Innovation Center, Tangshan 063210, China"],"raw_orcid":"https://orcid.org/0009-0004-2488-4768","affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, China","institution_ids":["https://openalex.org/I137506752"]},{"raw_affiliation_string":"Hebei Green Intelligent Mining Technology Innovation Center, Tangshan 063210, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101545665","display_name":"Xulong Yao","orcid":"https://orcid.org/0000-0001-9690-9603"},"institutions":[{"id":"https://openalex.org/I137506752","display_name":"North China University of Science and Technology","ror":"https://ror.org/04z4wmb81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137506752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xulong Yao","raw_affiliation_strings":["College of Mining Engineering, North China University of Science and Technology, Tangshan 063210, China","Hebei Green Intelligent Mining Technology Innovation Center, Tangshan 063210, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mining Engineering, North China University of Science and Technology, Tangshan 063210, China","institution_ids":["https://openalex.org/I137506752"]},{"raw_affiliation_string":"Hebei Green Intelligent Mining Technology Innovation Center, Tangshan 063210, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100732251","display_name":"Yanbo Zhang","orcid":"https://orcid.org/0000-0003-1054-9657"},"institutions":[{"id":"https://openalex.org/I137506752","display_name":"North China University of Science and Technology","ror":"https://ror.org/04z4wmb81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137506752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanbo Zhang","raw_affiliation_strings":["College of Mining Engineering, North China University of Science and Technology, Tangshan 063210, China","Hebei Green Intelligent Mining Technology Innovation Center, Tangshan 063210, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mining Engineering, North China University of Science and Technology, Tangshan 063210, China","institution_ids":["https://openalex.org/I137506752"]},{"raw_affiliation_string":"Hebei Green Intelligent Mining Technology Innovation Center, Tangshan 063210, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070170477","display_name":"Zhigang Tao","orcid":"https://orcid.org/0000-0002-8908-3038"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]},{"id":"https://openalex.org/I4391768053","display_name":"State Key Laboratory for Geomechanics and Deep Underground Engineering","ror":"https://ror.org/041818q22","country_code":"CN","type":"facility","lineage":["https://openalex.org/I25757504","https://openalex.org/I4391768053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigang Tao","raw_affiliation_strings":["School of Mechanical and Architectural Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China","State Key Laboratory for Geomechanics and Deep Underground Engineering, Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical and Architectural Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"State Key Laboratory for Geomechanics and Deep Underground Engineering, Beijing 100083, China","institution_ids":["https://openalex.org/I4391768053"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090826648","display_name":"Ling Peng","orcid":"https://orcid.org/0000-0002-1359-4982"},"institutions":[{"id":"https://openalex.org/I137506752","display_name":"North China University of Science and Technology","ror":"https://ror.org/04z4wmb81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137506752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Ling","raw_affiliation_strings":["College of Mining Engineering, North China University of Science and Technology, Tangshan 063210, China","Hebei Green Intelligent Mining Technology Innovation Center, Tangshan 063210, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mining Engineering, North China University of Science and Technology, Tangshan 063210, China","institution_ids":["https://openalex.org/I137506752"]},{"raw_affiliation_string":"Hebei Green Intelligent Mining Technology Innovation Center, Tangshan 063210, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101545665"],"corresponding_institution_ids":["https://openalex.org/I137506752"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":1.6203,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.80725979,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"23","issue":"20","first_page":"8513","last_page":"8513"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10161","display_name":"Rock Mechanics and Modeling","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T10161","display_name":"Rock Mechanics and Modeling","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T11609","display_name":"Geophysical Methods and Applications","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T10892","display_name":"Drilling and Well Engineering","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/acoustic-emission","display_name":"Acoustic emission","score":0.8041032552719116},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6626566052436829},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5749092102050781},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5394632816314697},{"id":"https://openalex.org/keywords/fracture","display_name":"Fracture (geology)","score":0.5251971483230591},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5245847105979919},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4460964500904083},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41954344511032104},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4187927842140198},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.40992581844329834},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.39304736256599426},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35302406549453735},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.2942165732383728},{"id":"https://openalex.org/keywords/geotechnical-engineering","display_name":"Geotechnical engineering","score":0.13343429565429688},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0905739963054657}],"concepts":[{"id":"https://openalex.org/C174598085","wikidata":"https://www.wikidata.org/wiki/Q746673","display_name":"Acoustic emission","level":2,"score":0.8041032552719116},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6626566052436829},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5749092102050781},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5394632816314697},{"id":"https://openalex.org/C43369102","wikidata":"https://www.wikidata.org/wiki/Q2307625","display_name":"Fracture (geology)","level":2,"score":0.5251971483230591},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5245847105979919},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4460964500904083},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41954344511032104},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4187927842140198},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.40992581844329834},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.39304736256599426},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35302406549453735},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2942165732383728},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.13343429565429688},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0905739963054657},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/s23208513","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23208513","pdf_url":"https://www.mdpi.com/1424-8220/23/20/8513/pdf?version=1697529454","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},{"id":"pmid:37896608","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37896608","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10610656","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10610656","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10610656/pdf/sensors-23-08513.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:c40184c6eb81443fac16deb84234dbc3","is_oa":true,"landing_page_url":"https://doaj.org/article/c40184c6eb81443fac16deb84234dbc3","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":"Sensors, Vol 23, Iss 20, p 8513 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s23208513","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23208513","pdf_url":"https://www.mdpi.com/1424-8220/23/20/8513/pdf?version=1697529454","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.7099999785423279}],"awards":[{"id":"https://openalex.org/G5710894527","display_name":null,"funder_award_id":"52074123","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7320889453","display_name":null,"funder_award_id":"No. E2021209148","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7622282931","display_name":null,"funder_award_id":"51804122","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8663282548","display_name":null,"funder_award_id":"51804122, 52074123","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":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387702856.pdf"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W321358065","https://openalex.org/W1572121205","https://openalex.org/W1964445786","https://openalex.org/W1977129889","https://openalex.org/W1989601311","https://openalex.org/W2004671628","https://openalex.org/W2008651536","https://openalex.org/W2012457675","https://openalex.org/W2093140299","https://openalex.org/W2108923552","https://openalex.org/W2123490915","https://openalex.org/W2151978417","https://openalex.org/W2411118237","https://openalex.org/W2611655888","https://openalex.org/W2622826443","https://openalex.org/W2624961743","https://openalex.org/W2727098128","https://openalex.org/W2735006420","https://openalex.org/W2761543231","https://openalex.org/W2799390666","https://openalex.org/W2884561390","https://openalex.org/W2918408501","https://openalex.org/W2941481989","https://openalex.org/W2950104029","https://openalex.org/W2959334635","https://openalex.org/W2963374347","https://openalex.org/W2963446712","https://openalex.org/W2968493457","https://openalex.org/W2971839280","https://openalex.org/W2982115656","https://openalex.org/W2995646679","https://openalex.org/W3016719260","https://openalex.org/W3024956434","https://openalex.org/W3080776956","https://openalex.org/W3106374739","https://openalex.org/W3140854437","https://openalex.org/W3169893408","https://openalex.org/W3171357516","https://openalex.org/W4205484185","https://openalex.org/W4207004698","https://openalex.org/W4211256381","https://openalex.org/W4295412947","https://openalex.org/W4296966543","https://openalex.org/W4307189368","https://openalex.org/W4311378113","https://openalex.org/W6714315767","https://openalex.org/W6745525703","https://openalex.org/W6793164127"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W2091753474","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2054591023","https://openalex.org/W3145507028","https://openalex.org/W3167935049","https://openalex.org/W2314189910","https://openalex.org/W3029198973"],"abstract_inverted_index":{"The":[0,22,210],"characteristics":[1,109],"of":[2,10,24,36,44,52,79,106,128,134,144,162,188,205,225,250,276,284,304],"acoustic":[3,25,45,81,125,163,193,278],"emission":[4,194,279],"signals":[5,85,195,280],"generated":[6,137],"in":[7,41,114,256,281],"the":[8,33,42,49,76,115,124,159,173,199,221,232,236,272,282,300],"process":[9,283],"rock":[11,20,37,53,129,139,166,189,285,305],"deformation":[12],"and":[13,31,48,92,110,153,178,191,198,202,228,242,267,294,299],"fission":[14],"contain":[15],"rich":[16],"information":[17,35,73],"on":[18,98,119,172],"internal":[19],"damage.":[21],"use":[23],"emissions":[26,46,82,126,164],"monitoring":[27,47],"technology":[28],"can":[29,219,290],"analyze":[30],"identify":[32],"precursor":[34,65,108,307],"failure.":[38],"At":[39],"present,":[40],"field":[43],"early":[50],"warning":[51],"fracture":[54,130,140,190,286,306],"disasters,":[55,91],"there":[56],"is":[57,69],"no":[58],"real-time":[59,104,185,222,274,301],"identification":[60],"method":[61],"for":[62,147,296],"a":[63,132,263],"disaster":[64,107],"characteristic":[66,77],"signal.":[67],"It":[68],"easy":[70],"to":[71,83,90,102,157],"lose":[72],"by":[74,138,246],"analyzing":[75],"parameters":[78],"traditional":[80,206],"find":[84],"that":[86,214],"serve":[87],"as":[88,131,261],"precursors":[89],"analysis":[93,151,156],"has":[94],"mostly":[95],"been":[96],"based":[97,171],"post-analysis,":[99],"which":[100,289],"leads":[101],"poor":[103],"recognition":[105,146,186,224,252,265,269,275,303],"low":[111],"application":[112],"levels":[113],"engineering":[116],"field.":[117],"Based":[118],"this,":[120],"this":[121,142,257],"paper":[122,258],"regards":[123],"signal":[127,136,251],"kind":[133],"speech":[135,145],"uses":[141],"idea":[143],"reference":[148],"alongside":[149],"spectral":[150],"(STFT)":[152],"Mel":[154],"frequency":[155],"realize":[158],"feature":[160],"extraction":[161],"from":[165],"fracture.":[167],"In":[168],"deep":[169],"learning,":[170],"VGG16":[174,207],"convolutional":[175,180],"neural":[176,181],"network":[177,200],"AlexNet":[179],"network,":[182],"six":[183,216],"intelligent":[184,223,273,302],"models":[187,218],"key":[192,226,277],"were":[196,208],"constructed,":[197],"structure":[201],"loss":[203],"function":[204],"optimized.":[209],"experimental":[211],"results":[212],"show":[213],"these":[215],"deep-learning":[217],"achieve":[220],"signals,":[227],"Mel,":[229],"combined":[230],"with":[231,239],"improved":[233],"VGG16,":[234],"achieved":[235],"best":[237],"performance":[238],"87.68%":[240],"accuracy":[241,266],"81.05%":[243],"recall.":[244],"Then,":[245],"comparing":[247],"multiple":[248],"groups":[249],"models,":[253],"Mel+VGG-FL":[254],"proposed":[255],"was":[259],"verified":[260],"having":[262],"high":[264],"certain":[268],"efficiency,":[270],"performing":[271],"more":[287],"accurately,":[288],"provide":[291],"new":[292],"ideas":[293],"methods":[295],"related":[297],"research":[298],"characteristics.":[308]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}