{"id":"https://openalex.org/W4285191322","doi":"https://doi.org/10.1109/access.2022.3186336","title":"Prediction of Burr Types in Drilling of Al-7075 Using Acoustic Emission and Convolution Neural Networks","display_name":"Prediction of Burr Types in Drilling of Al-7075 Using Acoustic Emission and Convolution Neural Networks","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285191322","doi":"https://doi.org/10.1109/access.2022.3186336"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3186336","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3186336","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09807282.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/ielx7/6287639/9668973/09807282.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101581764","display_name":"Hyojeong Kim","orcid":"https://orcid.org/0000-0002-4683-5287"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyojeong Kim","raw_affiliation_strings":["Department of Mechanical Design Engineering, Hanyang University, Seoul, South Korea","BK21 FOUR ERICA-ACE Center, Ansan, Gyeonggi-do, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-4683-5287","affiliations":[{"raw_affiliation_string":"Department of Mechanical Design Engineering, Hanyang University, Seoul, South Korea","institution_ids":["https://openalex.org/I4575257"]},{"raw_affiliation_string":"BK21 FOUR ERICA-ACE Center, Ansan, Gyeonggi-do, South Korea","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013610649","display_name":"Seoung Hwan Lee","orcid":"https://orcid.org/0000-0002-7726-2346"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seoung Hwan Lee","raw_affiliation_strings":["Department of Mechanical Engineering, BK21 FOUR ERICA-ACE Center, Ansan, Gyeonggi-do, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-7726-2346","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, BK21 FOUR ERICA-ACE Center, Ansan, Gyeonggi-do, South Korea","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.7739,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.65632194,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"10","issue":null,"first_page":"67826","last_page":"67838"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10188","display_name":"Advanced machining processes and optimization","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10188","display_name":"Advanced machining processes and optimization","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T11451","display_name":"Advanced Machining and Optimization Techniques","score":0.9994000196456909,"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/T11301","display_name":"Advanced Surface Polishing Techniques","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/drilling","display_name":"Drilling","score":0.6568891406059265},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6339433193206787},{"id":"https://openalex.org/keywords/machining","display_name":"Machining","score":0.5850145816802979},{"id":"https://openalex.org/keywords/acoustic-emission","display_name":"Acoustic emission","score":0.54010009765625},{"id":"https://openalex.org/keywords/drill","display_name":"Drill","score":0.5178292393684387},{"id":"https://openalex.org/keywords/laser-drilling","display_name":"Laser drilling","score":0.46808916330337524},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.4564800560474396},{"id":"https://openalex.org/keywords/tool-wear","display_name":"Tool wear","score":0.42064493894577026},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.3635467290878296},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.36142221093177795},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3501806855201721},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.3199402689933777},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25896787643432617}],"concepts":[{"id":"https://openalex.org/C25197100","wikidata":"https://www.wikidata.org/wiki/Q890886","display_name":"Drilling","level":2,"score":0.6568891406059265},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6339433193206787},{"id":"https://openalex.org/C523214423","wikidata":"https://www.wikidata.org/wiki/Q192047","display_name":"Machining","level":2,"score":0.5850145816802979},{"id":"https://openalex.org/C174598085","wikidata":"https://www.wikidata.org/wiki/Q746673","display_name":"Acoustic emission","level":2,"score":0.54010009765625},{"id":"https://openalex.org/C173736775","wikidata":"https://www.wikidata.org/wiki/Q58964","display_name":"Drill","level":2,"score":0.5178292393684387},{"id":"https://openalex.org/C2780997931","wikidata":"https://www.wikidata.org/wiki/Q6493062","display_name":"Laser drilling","level":3,"score":0.46808916330337524},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.4564800560474396},{"id":"https://openalex.org/C2776450708","wikidata":"https://www.wikidata.org/wiki/Q6008734","display_name":"Tool wear","level":3,"score":0.42064493894577026},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.3635467290878296},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.36142221093177795},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3501806855201721},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.3199402689933777},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25896787643432617},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3186336","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3186336","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09807282.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:63f2286bd7284b9f93dd3a2999e47b9a","is_oa":true,"landing_page_url":"https://doaj.org/article/63f2286bd7284b9f93dd3a2999e47b9a","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 10, Pp 67826-67838 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3186336","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3186336","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09807282.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":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4000000059604645}],"awards":[{"id":"https://openalex.org/G6562100603","display_name":null,"funder_award_id":"NRF-2020R1F1A1074814","funder_id":"https://openalex.org/F4320322030","funder_display_name":"Ministry of Science, ICT and Future Planning"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322030","display_name":"Ministry of Science, ICT and Future Planning","ror":"https://ror.org/032e49973"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285191322.pdf","grobid_xml":"https://content.openalex.org/works/W4285191322.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W831360126","https://openalex.org/W1470137088","https://openalex.org/W1564729204","https://openalex.org/W1584288698","https://openalex.org/W1970877822","https://openalex.org/W1972996214","https://openalex.org/W2013295396","https://openalex.org/W2017673773","https://openalex.org/W2020014449","https://openalex.org/W2025031481","https://openalex.org/W2075732010","https://openalex.org/W2086124007","https://openalex.org/W2112262218","https://openalex.org/W2128507408","https://openalex.org/W2130263579","https://openalex.org/W2135596289","https://openalex.org/W2155509221","https://openalex.org/W2193045105","https://openalex.org/W2404692435","https://openalex.org/W2495132988","https://openalex.org/W2547498804","https://openalex.org/W2569033697","https://openalex.org/W2613209044","https://openalex.org/W2618530766","https://openalex.org/W2768108646","https://openalex.org/W2784308021","https://openalex.org/W2786443194","https://openalex.org/W2809024381","https://openalex.org/W2883643760","https://openalex.org/W2884077485","https://openalex.org/W2965886282","https://openalex.org/W2970174347","https://openalex.org/W2974231072","https://openalex.org/W2974874966","https://openalex.org/W2988558713","https://openalex.org/W2999825681","https://openalex.org/W3005328894","https://openalex.org/W3009567396","https://openalex.org/W3018968744","https://openalex.org/W3028845928","https://openalex.org/W3114814413","https://openalex.org/W3174221070","https://openalex.org/W3179193383","https://openalex.org/W3184585050","https://openalex.org/W3197705536","https://openalex.org/W4211166028","https://openalex.org/W4220925901","https://openalex.org/W4252227190","https://openalex.org/W6724050607"],"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/W2158646189","https://openalex.org/W2091753474","https://openalex.org/W72982894","https://openalex.org/W1964452093"],"abstract_inverted_index":{"The":[0,135,237],"formation":[1,76],"of":[2,8,45,77,82,116,153,157],"exit":[3,101,117],"burrs":[4,24,46,78,118,122],"during":[5,79,180],"the":[6,42,75,80,89,96,99,131,151,154,158,162,176,207,233,271,285,292],"drilling":[7,23,55,81,97,159,181,208,244],"ductile":[9],"metals":[10],"such":[11,104],"as":[12,105,213,282],"aluminum":[13,132],"is":[14,71,85,240],"critical":[15],"in":[16,88,242],"precision":[17],"manufacturing":[18,20,280],"and":[19,62,91,108,125,145,196,210,254],"automation.":[21],"Because":[22],"are":[25,263],"difficult":[26],"to":[27,30,73,174,227],"remove,":[28],"methods":[29],"predict":[31,74],"various":[32,43],"burr":[33,37,102,106,142,163,182,185,245,286],"types":[34,115,186,246,287],"and/or":[35],"implement":[36],"minimization":[38],"schemes":[39],"that":[40],"consider":[41],"attributes":[44],"must":[47],"be":[48],"devised.":[49],"In":[50,269],"this":[51],"study,":[52],"not":[53],"only":[54],"process":[56,281],"conditions,":[57,98],"including":[58],"feed,":[59],"cutting":[60],"speed,":[61],"drill":[63],"diameter,":[64],"but":[65],"also":[66],"an":[67,146],"artificial":[68,190,256],"neural":[69,202,222],"network":[70,223,294],"implemented":[72,226],"aluminum-7075,":[83],"which":[84,149],"widely":[86],"used":[87],"aerospace":[90],"automobile":[92],"industries.":[93],"Based":[94],"on":[95],"main":[100],"characteristics,":[103],"size":[107],"type,":[109],"were":[110,128,138,187,204],"classified":[111],"experimentally.":[112],"Three":[113],"different":[114],"(uniform":[119],"burrs,":[120],"uniform":[121],"with":[123,266,288],"caps,":[124],"transient":[126],"burrs)":[127],"observed":[129],"from":[130,232],"7075":[133],"workpieces.":[134],"classification":[136],"results":[137,262],"further":[139],"analyzed":[140],"using":[141,189,206],"control":[143],"charts":[144],"empirical":[147],"equation,":[148],"enables":[150],"understanding":[152],"overall":[155],"influence":[156],"conditions":[160,209],"over":[161,297],"types.":[164],"Moreover,":[165],"acoustic":[166],"emission":[167],"(AE)":[168],"sensor":[169,251],"monitoring":[170,252],"scheme":[171,239],"was":[172,225],"utilized":[173],"sample":[175],"sensitive":[177,250],"time-series":[178],"signals":[179,212],"formation.":[183],"Subsequently,":[184],"predicted":[188],"intelligence":[191,257],"techniques,":[192,258],"namely":[193],"machining":[194],"learning":[195],"deep":[197],"learning.":[198],"First,":[199],"backpropagation":[200],"(BP)":[201],"networks":[203],"constructed":[205],"AE":[211,235],"input":[214],"vectors.":[215],"For":[216],"a":[217,220,249,277],"comparative":[218],"prediction,":[219],"convolution":[221],"(CNN)":[224],"obtain":[228],"spectrogram":[229],"image":[230],"inputs":[231],"sampled":[234],"data.":[236],"proposed":[238],"useful":[241],"predicting":[243],"by":[247],"employing":[248],"setup":[253],"advanced":[255],"where":[259],"both":[260],"prediction":[261],"well":[264],"matched":[265],"experimental":[267],"results.":[268],"addition,":[270],"CNN":[272],"model":[273,295],"shows":[274],"effectiveness":[275],"for":[276],"commonly":[278],"practiced":[279],"it":[283],"predicts":[284],"better":[289],"accuracy":[290],"than":[291],"BP":[293],"(0.9375":[296],"0.8571).":[298]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
