{"id":"https://openalex.org/W3082810877","doi":"https://doi.org/10.3390/s20174896","title":"Deep Anomaly Detection for CNC Machine Cutting Tool Using Spindle Current Signals","display_name":"Deep Anomaly Detection for CNC Machine Cutting Tool Using Spindle Current Signals","publication_year":2020,"publication_date":"2020-08-29","ids":{"openalex":"https://openalex.org/W3082810877","doi":"https://doi.org/10.3390/s20174896","mag":"3082810877","pmid":"https://pubmed.ncbi.nlm.nih.gov/32872525"},"language":"en","primary_location":{"id":"doi:10.3390/s20174896","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20174896","pdf_url":"https://www.mdpi.com/1424-8220/20/17/4896/pdf?version=1598947236","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/1424-8220/20/17/4896/pdf?version=1598947236","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100765203","display_name":"Guang Li","orcid":"https://orcid.org/0000-0002-0698-6822"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guang Li","raw_affiliation_strings":["Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China"],"raw_orcid":"https://orcid.org/0000-0002-0698-6822","affiliations":[{"raw_affiliation_string":"Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032399729","display_name":"Yan Fu","orcid":"https://orcid.org/0000-0003-1864-2071"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I4210096250","display_name":"Beijing Institute of Big Data Research","ror":"https://ror.org/00s1sz824","country_code":"CN","type":"facility","lineage":["https://openalex.org/I20231570","https://openalex.org/I37796252","https://openalex.org/I4210096250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Fu","raw_affiliation_strings":["Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China","Union Big Data, Chengdu 610000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"Union Big Data, Chengdu 610000, China","institution_ids":["https://openalex.org/I4210096250"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029425733","display_name":"Duanbing Chen","orcid":"https://orcid.org/0000-0003-2239-3012"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I4210096250","display_name":"Beijing Institute of Big Data Research","ror":"https://ror.org/00s1sz824","country_code":"CN","type":"facility","lineage":["https://openalex.org/I20231570","https://openalex.org/I37796252","https://openalex.org/I4210096250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Duanbing Chen","raw_affiliation_strings":["Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China","Union Big Data, Chengdu 610000, China"],"raw_orcid":"https://orcid.org/0000-0003-2239-3012","affiliations":[{"raw_affiliation_string":"Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"Union Big Data, Chengdu 610000, China","institution_ids":["https://openalex.org/I4210096250"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102311405","display_name":"Lulu Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lulu Shi","raw_affiliation_strings":["Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101411166","display_name":"Junlin Zhou","orcid":"https://orcid.org/0000-0002-9575-2533"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I4210096250","display_name":"Beijing Institute of Big Data Research","ror":"https://ror.org/00s1sz824","country_code":"CN","type":"facility","lineage":["https://openalex.org/I20231570","https://openalex.org/I37796252","https://openalex.org/I4210096250"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junlin Zhou","raw_affiliation_strings":["Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China","Union Big Data, Chengdu 610000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"Union Big Data, Chengdu 610000, China","institution_ids":["https://openalex.org/I4210096250"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101411166"],"corresponding_institution_ids":["https://openalex.org/I150229711","https://openalex.org/I4210096250"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":2.9986,"has_fulltext":true,"cited_by_count":42,"citation_normalized_percentile":{"value":0.92929424,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"20","issue":"17","first_page":"4896","last_page":"4896"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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":0.9740999937057495,"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/breakage","display_name":"Breakage","score":0.8527486324310303},{"id":"https://openalex.org/keywords/numerical-control","display_name":"Numerical control","score":0.7153350114822388},{"id":"https://openalex.org/keywords/machine-tool","display_name":"Machine tool","score":0.6265725493431091},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5547418594360352},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45378586649894714},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4297485947608948},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42951327562332153},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3945927619934082},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3359013795852661},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3228130340576172},{"id":"https://openalex.org/keywords/machining","display_name":"Machining","score":0.2245153784751892},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.13517922163009644}],"concepts":[{"id":"https://openalex.org/C2779015675","wikidata":"https://www.wikidata.org/wiki/Q92796261","display_name":"Breakage","level":2,"score":0.8527486324310303},{"id":"https://openalex.org/C175457265","wikidata":"https://www.wikidata.org/wiki/Q190247","display_name":"Numerical control","level":3,"score":0.7153350114822388},{"id":"https://openalex.org/C5941749","wikidata":"https://www.wikidata.org/wiki/Q19768","display_name":"Machine tool","level":2,"score":0.6265725493431091},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5547418594360352},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45378586649894714},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4297485947608948},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42951327562332153},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3945927619934082},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3359013795852661},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3228130340576172},{"id":"https://openalex.org/C523214423","wikidata":"https://www.wikidata.org/wiki/Q192047","display_name":"Machining","level":2,"score":0.2245153784751892},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.13517922163009644},{"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/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s20174896","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20174896","pdf_url":"https://www.mdpi.com/1424-8220/20/17/4896/pdf?version=1598947236","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:32872525","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32872525","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:doaj.org/article:cddd8feb258f462db4711791a90e8bac","is_oa":true,"landing_page_url":"https://doaj.org/article/cddd8feb258f462db4711791a90e8bac","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 20, Iss 17, p 4896 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/20/17/4896/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s20174896","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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; Volume 20; Issue 17; Pages: 4896","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7506642","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7506642","pdf_url":null,"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"}],"best_oa_location":{"id":"doi:10.3390/s20174896","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20174896","pdf_url":"https://www.mdpi.com/1424-8220/20/17/4896/pdf?version=1598947236","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":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3082810877.pdf","grobid_xml":"https://content.openalex.org/works/W3082810877.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1972553459","https://openalex.org/W1983532561","https://openalex.org/W1987326707","https://openalex.org/W2066695323","https://openalex.org/W2092150674","https://openalex.org/W2097117768","https://openalex.org/W2102543906","https://openalex.org/W2105497548","https://openalex.org/W2112796928","https://openalex.org/W2122646361","https://openalex.org/W2144094032","https://openalex.org/W2146066328","https://openalex.org/W2163605009","https://openalex.org/W2165698076","https://openalex.org/W2194775991","https://openalex.org/W2355427712","https://openalex.org/W2521656013","https://openalex.org/W2556513903","https://openalex.org/W2586186134","https://openalex.org/W2601600520","https://openalex.org/W2605910748","https://openalex.org/W2618579378"],"related_works":["https://openalex.org/W3155968943","https://openalex.org/W2921978471","https://openalex.org/W2380506268","https://openalex.org/W2390059556","https://openalex.org/W2373654783","https://openalex.org/W2393858310","https://openalex.org/W2394442851","https://openalex.org/W2356921929","https://openalex.org/W2891744532","https://openalex.org/W2352157619"],"abstract_inverted_index":{"In":[0,33,62,87],"recent":[1],"years,":[2],"industrial":[3,19],"production":[4,20,27],"has":[5,145],"become":[6],"more":[7,9],"and":[8,29,111,119,144],"automated.":[10],"Machine":[11],"cutting":[12],"tool":[13,38,55,76,85,130],"as":[14],"an":[15,43],"important":[16],"part":[17],"of":[18,31,53,75,84,102],"have":[21],"a":[22,34,49,117],"large":[23],"impact":[24],"on":[25],"the":[26,54,59,65,73,92,108,126,138],"efficiency":[28],"costs":[30],"products.":[32],"real":[35],"manufacturing":[36],"process,":[37],"breakage":[39,56,77,131],"often":[40],"occurs":[41],"in":[42,129],"instant":[44],"without":[45],"warning,":[46],"which":[47,79],"results":[48,80],"extremely":[50],"unbalanced":[51],"ratio":[52],"samples":[57],"to":[58,81,97,124],"normal":[60],"ones.":[61],"this":[63,88],"case,":[64],"traditional":[66],"supervised":[67],"learning":[68,113],"model":[69],"can":[70,141],"not":[71],"fit":[72],"sample":[74],"well,":[78],"inaccurate":[82],"prediction":[83,136],"breakage.":[86],"paper,":[89],"we":[90,115],"use":[91],"high":[93],"precision":[94],"Hall":[95],"sensor":[96],"collect":[98],"spindle":[99],"current":[100],"data":[101],"computer":[103],"numerical":[104],"control":[105],"(CNC).":[106],"Combining":[107],"anomaly":[109],"detection":[110],"deep":[112],"methods,":[114],"propose":[116],"simple":[118],"novel":[120],"method":[121,140],"called":[122],"CNN-AD":[123],"solve":[125],"class-imbalance":[127],"problem":[128],"prediction.":[132],"Compared":[133],"with":[134],"other":[135],"algorithms,":[137],"proposed":[139],"converge":[142],"faster":[143],"better":[146],"accuracy.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
