{"id":"https://openalex.org/W3137356341","doi":"https://doi.org/10.1115/1.4050531","title":"Tool Wear Online Monitoring Method Based on DT and SSAE-PHMM","display_name":"Tool Wear Online Monitoring Method Based on DT and SSAE-PHMM","publication_year":2021,"publication_date":"2021-03-13","ids":{"openalex":"https://openalex.org/W3137356341","doi":"https://doi.org/10.1115/1.4050531","mag":"3137356341"},"language":"en","primary_location":{"id":"doi:10.1115/1.4050531","is_oa":false,"landing_page_url":"https://doi.org/10.1115/1.4050531","pdf_url":null,"source":{"id":"https://openalex.org/S173178594","display_name":"Journal of Computing and Information Science in Engineering","issn_l":"1530-9827","issn":["1530-9827","1944-7078"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316053","host_organization_name":"ASM International","host_organization_lineage":["https://openalex.org/P4310316053"],"host_organization_lineage_names":["ASM International"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing and Information Science in Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100362451","display_name":"Xiangyu Zhang","orcid":"https://orcid.org/0000-0001-8415-0003"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyu Zhang","raw_affiliation_strings":["School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010502314","display_name":"Lilan Liu","orcid":"https://orcid.org/0009-0006-4186-1538"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lilan Liu","raw_affiliation_strings":["School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030367905","display_name":"Xiang Wan","orcid":"https://orcid.org/0000-0002-2324-6527"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Wan","raw_affiliation_strings":["School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100557209","display_name":"Bowen Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowen Feng","raw_affiliation_strings":["School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":null,"apc_paid":null,"fwci":2.7067,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.89600944,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"21","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10188","display_name":"Advanced machining processes and optimization","score":0.9973999857902527,"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":0.9973999857902527,"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":0.9916999936103821,"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/T11159","display_name":"Manufacturing Process and Optimization","score":0.9477999806404114,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/tool-wear","display_name":"Tool wear","score":0.7643760442733765},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6054956316947937},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5730541348457336},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5664024353027344},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5410773158073425},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4246673583984375},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4190249443054199},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4188958406448364},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3686429560184479},{"id":"https://openalex.org/keywords/machining","display_name":"Machining","score":0.314132958650589},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24295175075531006}],"concepts":[{"id":"https://openalex.org/C2776450708","wikidata":"https://www.wikidata.org/wiki/Q6008734","display_name":"Tool wear","level":3,"score":0.7643760442733765},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6054956316947937},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5730541348457336},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5664024353027344},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5410773158073425},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4246673583984375},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4190249443054199},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4188958406448364},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3686429560184479},{"id":"https://openalex.org/C523214423","wikidata":"https://www.wikidata.org/wiki/Q192047","display_name":"Machining","level":2,"score":0.314132958650589},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24295175075531006},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1115/1.4050531","is_oa":false,"landing_page_url":"https://doi.org/10.1115/1.4050531","pdf_url":null,"source":{"id":"https://openalex.org/S173178594","display_name":"Journal of Computing and Information Science in Engineering","issn_l":"1530-9827","issn":["1530-9827","1944-7078"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316053","host_organization_name":"ASM International","host_organization_lineage":["https://openalex.org/P4310316053"],"host_organization_lineage_names":["ASM International"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing and Information Science in Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"display_name":"No poverty","id":"https://metadata.un.org/sdg/1"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W635507760","https://openalex.org/W1982542997","https://openalex.org/W1998735544","https://openalex.org/W2007321142","https://openalex.org/W2038338100","https://openalex.org/W2104381957","https://openalex.org/W2113333841","https://openalex.org/W2558443896","https://openalex.org/W2575828067","https://openalex.org/W2588912331","https://openalex.org/W2603304445","https://openalex.org/W2770233526","https://openalex.org/W2810813609","https://openalex.org/W2846912879","https://openalex.org/W2883267225","https://openalex.org/W2935904262","https://openalex.org/W2979111538","https://openalex.org/W3000593332","https://openalex.org/W3003384280","https://openalex.org/W3036256228","https://openalex.org/W6675611879"],"related_works":["https://openalex.org/W2364370872","https://openalex.org/W2097963413","https://openalex.org/W2025614924","https://openalex.org/W2735765216","https://openalex.org/W3145575561","https://openalex.org/W2995886640","https://openalex.org/W1591475660","https://openalex.org/W2294335174","https://openalex.org/W2549972263","https://openalex.org/W4319073490"],"abstract_inverted_index":{"Abstract":[0],"The":[1],"real-time":[2,46,186],"requirements":[3],"of":[4,50,60,91,151,159,166,175,181,200],"tool":[5,18,65,93,98,114,135,152,188],"wear":[6,19,66,99,115,136,153,189],"states":[7],"monitoring":[8,20,67,194],"are":[9],"getting":[10],"higher":[11],"and":[12,54,72,96,106,162,170,183,191,197],"higher,":[13],"at":[14],"the":[15,32,43,55,88,92,97,109,157,173,178,198],"same":[16],"time,":[17],"lacks":[21],"a":[22,83,113,144],"modeling":[23],"data":[24,57],"comprehensive":[25],"carrier,":[26],"which":[27,85,124],"hinders":[28],"its":[29],"application":[30],"in":[31,108],"actual":[33],"machining":[34],"process.":[35],"In":[36],"order":[37],"to":[38,147],"solve":[39],"this":[40,201],"problem,":[41],"combining":[42],"high":[44],"fidelity":[45],"behavior":[47],"simulation":[48],"characteristics":[49],"digital":[51],"twin":[52],"(DT)":[53],"powerful":[56],"mining":[58],"capabilities":[59],"artificial":[61,167,184],"intelligence,":[62,185],"an":[63],"online":[64,193],"method":[68,202],"based":[69,119],"on":[70,120],"DT":[71,84,182],"Stack":[73],"Sparse":[74],"Auto-Encoder-parallel":[75],"hidden":[76],"Markov":[77],"model":[78,118,146],"(SSAE-PHMM)":[79],"was":[80,94,101,122,195,203],"proposed.":[81],"First,":[82],"can":[86,125],"reflect":[87],"real":[89],"state":[90,100,116],"established,":[95,123],"predicted":[102],"by":[103,205],"visual":[104],"display":[105],"analysis":[107],"virtual":[110],"space;":[111],"Second,":[112],"recognition":[117,150],"SSAE-PHMM":[121],"adaptively":[126],"complete":[127],"time":[128,165],"domain":[129],"feature":[130],"extraction.":[131],"And":[132],"for":[133],"each":[134],"state,":[137],"multiple":[138],"HMM":[139],"models":[140],"were":[141],"combined":[142],"into":[143],"PHMM":[145,155],"realize":[148],"accurate":[149],"state.":[154],"overcome":[156],"defects":[158],"poor":[160],"convergence":[161],"long":[163],"training":[164],"neural":[168],"network,":[169],"greatly":[171],"improved":[172],"performance":[174],"classifier.":[176],"Through":[177],"deep":[179],"integration":[180],"data-driven":[187],"qualitative":[190],"quantitative":[192],"realized,":[196],"effectiveness":[199],"verified":[204],"experiments.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}