{"id":"https://openalex.org/W4399021333","doi":"https://doi.org/10.1155/2024/3717867","title":"Recognition Algorithm of AE Signal of Rock Fracture Based on Multiscale 1DCNN-BLSTM","display_name":"Recognition Algorithm of AE Signal of Rock Fracture Based on Multiscale 1DCNN-BLSTM","publication_year":2024,"publication_date":"2024-05-24","ids":{"openalex":"https://openalex.org/W4399021333","doi":"https://doi.org/10.1155/2024/3717867"},"language":"en","primary_location":{"id":"doi:10.1155/2024/3717867","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2024/3717867","pdf_url":"https://downloads.hindawi.com/journals/jece/2024/3717867.pdf","source":{"id":"https://openalex.org/S174662166","display_name":"Journal of Electrical and Computer Engineering","issn_l":"2090-0147","issn":["2090-0147","2090-0155"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electrical and Computer Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://downloads.hindawi.com/journals/jece/2024/3717867.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030319477","display_name":"Weihua Wang","orcid":"https://orcid.org/0000-0003-1614-0166"},"institutions":[{"id":"https://openalex.org/I4210154710","display_name":"Wuxi Taihu Hospital","ror":"https://ror.org/05qp6pd10","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210154710"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weihua Wang","raw_affiliation_strings":["School of Intelligent Equipment Engineering, Wuxi Taihu University, Wuxi, China"],"raw_orcid":"https://orcid.org/0000-0003-1614-0166","affiliations":[{"raw_affiliation_string":"School of Intelligent Equipment Engineering, Wuxi Taihu University, Wuxi, China","institution_ids":["https://openalex.org/I4210154710"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5030319477"],"corresponding_institution_ids":["https://openalex.org/I4210154710"],"apc_list":{"value":1400,"currency":"USD","value_usd":1400},"apc_paid":{"value":1400,"currency":"USD","value_usd":1400},"fwci":0.6601,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66033151,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"2024","issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14392","display_name":"Geoscience and Mining Technology","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T14392","display_name":"Geoscience and Mining Technology","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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":0.9872000217437744,"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/T10161","display_name":"Rock Mechanics and Modeling","score":0.9837999939918518,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.6174362897872925},{"id":"https://openalex.org/keywords/fracture","display_name":"Fracture (geology)","score":0.5961176753044128},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49216288328170776},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44042131304740906},{"id":"https://openalex.org/keywords/acoustic-emission","display_name":"Acoustic emission","score":0.431369423866272},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38261014223098755},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30077627301216125},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.24082306027412415},{"id":"https://openalex.org/keywords/composite-material","display_name":"Composite material","score":0.18928241729736328}],"concepts":[{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.6174362897872925},{"id":"https://openalex.org/C43369102","wikidata":"https://www.wikidata.org/wiki/Q2307625","display_name":"Fracture (geology)","level":2,"score":0.5961176753044128},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49216288328170776},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44042131304740906},{"id":"https://openalex.org/C174598085","wikidata":"https://www.wikidata.org/wiki/Q746673","display_name":"Acoustic emission","level":2,"score":0.431369423866272},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38261014223098755},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30077627301216125},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.24082306027412415},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.18928241729736328},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/2024/3717867","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2024/3717867","pdf_url":"https://downloads.hindawi.com/journals/jece/2024/3717867.pdf","source":{"id":"https://openalex.org/S174662166","display_name":"Journal of Electrical and Computer Engineering","issn_l":"2090-0147","issn":["2090-0147","2090-0155"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electrical and Computer Engineering","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d70ab0d4387b444f92d9ce09697f60f3","is_oa":true,"landing_page_url":"https://doaj.org/article/d70ab0d4387b444f92d9ce09697f60f3","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":"Journal of Electrical and Computer Engineering, Vol 2024 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2024/3717867","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2024/3717867","pdf_url":"https://downloads.hindawi.com/journals/jece/2024/3717867.pdf","source":{"id":"https://openalex.org/S174662166","display_name":"Journal of Electrical and Computer Engineering","issn_l":"2090-0147","issn":["2090-0147","2090-0155"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electrical and Computer Engineering","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399021333.pdf"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W2087883254","https://openalex.org/W2524832738","https://openalex.org/W2606828341","https://openalex.org/W2620688529","https://openalex.org/W2766060287","https://openalex.org/W2767035496","https://openalex.org/W3022952790","https://openalex.org/W3035372852","https://openalex.org/W3153998777","https://openalex.org/W4200568183","https://openalex.org/W4210656461","https://openalex.org/W4220871741","https://openalex.org/W4241746003"],"related_works":["https://openalex.org/W2393097294","https://openalex.org/W2889442519","https://openalex.org/W2381188978","https://openalex.org/W2364223432","https://openalex.org/W2988080746","https://openalex.org/W2377260462","https://openalex.org/W2091753474","https://openalex.org/W2054591023","https://openalex.org/W3145507028","https://openalex.org/W2314189910"],"abstract_inverted_index":{"Acoustic":[0],"emission":[1,26,53,72,136],"(AE)":[2],"signals":[3,54],"produced":[4],"by":[5],"different":[6,11,60,103],"types":[7],"of":[8,13,20,28,37,70,102,105,111,147,186,197],"rocks":[9],"have":[10],"characteristics":[12,27,69],"information.":[14],"Determining":[15],"the":[16,24,34,67,91,108,112,114,134,141,144,163,177,195],"brittle":[17,61],"mineral":[18,62],"content":[19],"rock":[21,29,38,57,198],"according":[22],"to":[23,32,50,66,99,119],"acoustic":[25,52,71,135],"is":[30],"helpful":[31],"understand":[33],"mechanical":[35],"behavior":[36],"in":[39,168],"field":[40],"monitoring.":[41],"This":[42],"article":[43],"constructs":[44],"a":[45,75,172,190],"deep":[46],"learning":[47],"algorithm":[48],"model":[49,166],"identify":[51],"released":[55],"from":[56,133],"fractures":[58],"with":[59,82,157],"contents.":[63],"In":[64,107],"response":[65],"interference":[68],"signal":[73,137],"data,":[74],"multiscale":[76,94,164],"one-dimensional":[77],"convolutional":[78,95],"neural":[79],"network":[80,116],"embedded":[81,167],"efficient":[83],"channel":[84],"attention":[85],"(ECA)":[86],"module":[87,170],"was":[88,117],"incorporated":[89,118],"into":[90],"model,":[92,113],"and":[93,128,176],"kernels":[96],"were":[97],"used":[98],"extract":[100,120],"features":[101,132],"levels":[104],"precision.":[106],"latter":[109],"half":[110],"BLSTM":[115],"time":[121],"series-related":[122],"features,":[123,127],"local":[124],"spatial":[125],"uncorrelated":[126],"weak":[129],"periodic":[130],"pattern":[131],"data.":[138],"To":[139],"solve":[140],"problem":[142],"that":[143,162],"recognition":[145,178],"accuracy":[146,179],"minority":[148],"samples":[149],"decreases,":[150],"this":[151,187],"study":[152],"replaces":[153],"ReLU":[154],"activation":[155],"function":[156],"SELU.":[158],"The":[159,184],"results":[160],"show":[161],"1DCNN-BLSTM":[165],"ECA":[169],"has":[171],"good":[173],"antinoise":[174],"performance,":[175],"can":[180],"reach":[181],"over":[182],"90%.":[183],"discovery":[185],"work":[188],"provides":[189],"new":[191],"idea":[192],"for":[193],"exploring":[194],"mechanism":[196],"mass":[199],"instability.":[200]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
