{"id":"https://openalex.org/W4285152355","doi":"https://doi.org/10.1109/access.2022.3176900","title":"A Model-Data-Fusion Pole Piece Thickness Prediction Method With Multisensor Fusion for Lithium Battery Rolling Machine","display_name":"A Model-Data-Fusion Pole Piece Thickness Prediction Method With Multisensor Fusion for Lithium Battery Rolling Machine","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285152355","doi":"https://doi.org/10.1109/access.2022.3176900"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3176900","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3176900","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09779730.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/ielx7/6287639/6514899/09779730.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078883262","display_name":"Yanjun Xiao","orcid":"https://orcid.org/0000-0003-3299-9069"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanjun Xiao","raw_affiliation_strings":["Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles, School of Mechanical Engineering, Hebei University of Technology, Tianjin, China","School of Mechanical Engineering, Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles, Hebei University of Technology, Tianjin, China and Career Leader Intelligent Control Automation Company, Suqian 223800, Jiangsu Province, China and School of Mechanical Engineering, Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-3299-9069","affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles, School of Mechanical Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]},{"raw_affiliation_string":"School of Mechanical Engineering, Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles, Hebei University of Technology, Tianjin, China and Career Leader Intelligent Control Automation Company, Suqian 223800, Jiangsu Province, China and School of Mechanical Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082649374","display_name":"Shuhan Deng","orcid":"https://orcid.org/0000-0001-5112-8934"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhan Deng","raw_affiliation_strings":["School of Mechanical Engineering, Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-5112-8934","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053086655","display_name":"Han Fu-rong","orcid":"https://orcid.org/0000-0002-9475-9485"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Furong Han","raw_affiliation_strings":["Career Leader Intelligent Control Automation Company, Suqian, Jiangsu, China","Career Leader Intelligent Control Automation Company, Suqian 223800, Jiangsu Province, China and School of Mechanical Engineering, Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-9475-9485","affiliations":[{"raw_affiliation_string":"Career Leader Intelligent Control Automation Company, Suqian, Jiangsu, China","institution_ids":["https://openalex.org/I4210094879"]},{"raw_affiliation_string":"Career Leader Intelligent Control Automation Company, Suqian 223800, Jiangsu Province, China and School of Mechanical Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015557819","display_name":"Xiaoliang Wang","orcid":"https://orcid.org/0000-0002-3688-4851"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoliang Wang","raw_affiliation_strings":["School of Mechanical Engineering, Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-3688-4851","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zonghua Zhang","orcid":"https://orcid.org/0000-0002-3331-0107"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zonghua Zhang","raw_affiliation_strings":["School of Mechanical Engineering, Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-3331-0107","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076612564","display_name":"Kai Peng","orcid":"https://orcid.org/0009-0006-8157-0831"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Peng","raw_affiliation_strings":["School of Mechanical Engineering, Hebei University of Technology, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"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":0.3136,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.53280326,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"10","issue":null,"first_page":"55034","last_page":"55050"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10663","display_name":"Advanced Battery Technologies Research","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10663","display_name":"Advanced Battery Technologies Research","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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":0.9685999751091003,"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"}},{"id":"https://openalex.org/T13717","display_name":"Advanced Algorithms and Applications","score":0.9646999835968018,"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/computer-science","display_name":"Computer science","score":0.7058144807815552},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5560328364372253},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5450530052185059},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.5278774499893188},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5132095813751221},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5114446878433228},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4529002904891968},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.45119616389274597},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37576553225517273},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09656950831413269},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08802571892738342}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7058144807815552},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5560328364372253},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5450530052185059},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.5278774499893188},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5132095813751221},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5114446878433228},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4529002904891968},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.45119616389274597},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37576553225517273},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09656950831413269},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08802571892738342},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3176900","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3176900","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09779730.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:33f17d5fa2b34fd68e8a93e0781ca9f8","is_oa":true,"landing_page_url":"https://doaj.org/article/33f17d5fa2b34fd68e8a93e0781ca9f8","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 55034-55050 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3176900","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3176900","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09779730.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":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.6800000071525574}],"awards":[{"id":"https://openalex.org/G2844625335","display_name":null,"funder_award_id":"BRA2020244","funder_id":"https://openalex.org/F4320321605","funder_display_name":"Government of Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285152355.pdf","grobid_xml":"https://content.openalex.org/works/W4285152355.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W2048868027","https://openalex.org/W2332786858","https://openalex.org/W2584608705","https://openalex.org/W2739791970","https://openalex.org/W2888951026","https://openalex.org/W2911527855","https://openalex.org/W2916708014","https://openalex.org/W2940523805","https://openalex.org/W2951288548","https://openalex.org/W2998503861","https://openalex.org/W3047640888","https://openalex.org/W3086572651","https://openalex.org/W3090011050","https://openalex.org/W3093879950","https://openalex.org/W3094557230","https://openalex.org/W3110921317","https://openalex.org/W3127692495","https://openalex.org/W3128596107","https://openalex.org/W3170411645","https://openalex.org/W3182506373","https://openalex.org/W3188369435","https://openalex.org/W3194307377","https://openalex.org/W3202317291","https://openalex.org/W4205933014","https://openalex.org/W4206512511","https://openalex.org/W4213138287","https://openalex.org/W4214703140","https://openalex.org/W4220986405"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4220972140","https://openalex.org/W3161120485","https://openalex.org/W4387968020","https://openalex.org/W2150029999","https://openalex.org/W2122216001"],"abstract_inverted_index":{"Trend":[0],"prediction":[1,64,73,91,195,277],"based":[2,75],"on":[3,76],"sensor":[4,101,144],"data":[5,57,98,141,229,263],"is":[6,173],"an":[7],"important":[8],"topic":[9],"in":[10,42,226],"the":[11,21,43,63,104,111,121,126,131,135,140,153,156,160,165,176,181,188,191,199,217,220,255,260,265,276],"thickness":[12,47,136,266],"control":[13,48,53,137,193,267],"system":[14,54,194,268],"of":[15,23,37,52,92,106,114,125,155,159,183,190,201,212,219,228,264,269],"lithium":[16,44,93,270],"battery":[17,45,94,115,271],"electrode":[18,46,95,107,116,272],"mills.":[19],"As":[20],"number":[22],"sensors":[24],"increases,":[25],"we":[26,119,147],"can":[27,257],"measure":[28],"and":[29,32,40,56,81,100,109,138,143,163,197,205,232,274],"store":[30],"more":[31,33],"data.":[34,250],"The":[35,50,251],"characteristics":[36,154],"nonlinearity,":[38],"uncertainty,":[39],"time-variability":[41],"system.":[49],"increase":[51],"complexity":[55],"volume":[58],"does":[59],"not":[60],"effectively":[61,258],"improve":[62,110,187,275],"performance.":[65,278],"This":[66],"paper":[67],"proposes":[68],"a":[69,77],"physical-data":[70],"fusion":[71,177],"modeling":[72],"method":[74,150],"multiform":[78],"coupling":[79],"model":[80,124,196,223,233,259],"Bayesian":[82,149,166,242],"LSTM":[83,167,243],"(Bayesian":[84],"Long":[85],"Short-Term":[86],"Memory)":[87],"to":[88,128,151,179,186,207],"achieve":[89],"dynamic":[90],"thickness,":[96,108],"overcome":[97,139],"irrelevance":[99,142],"noise,":[102],"ensure":[103],"consistency":[105],"operational":[112],"efficiency":[113],"production:":[117],"Firstly,":[118],"establish":[120],"underlying":[122],"physical":[123],"roll":[127],"further":[129],"obtain":[130,152],"specific":[132],"parameters":[133],"affecting":[134],"noise;":[145],"secondly,":[146],"use":[148],"weight":[157],"distribution":[158],"sub-prediction":[161],"network":[162,240],"construct":[164],"predictor.":[168],"An":[169],"MLP":[170],"(Multilayer":[171],"Perceptron)":[172],"used":[174],"as":[175],"layer":[178],"fuse":[180],"results":[182,252],"different":[184],"sub-predictions":[185],"robustness":[189],"nonlinear":[192],"solve":[198],"problems":[200],"slow":[202],"approximation":[203],"speed":[204],"ease":[206],"fall":[208],"into":[209],"local":[210],"minimization":[211],"traditional":[213],"neural":[214,239],"networks.":[215],"Finally,":[216],"advantages":[218],"deep":[221],"learning":[222],"are":[224],"analyzed":[225],"terms":[227],"feature":[230],"self-extraction":[231],"generalization":[234],"generalizability.":[235],"Compared":[236],"with":[237],"other":[238],"models,":[241],"has":[244],"better":[245],"generalizability":[246],"for":[247],"small":[248],"sample":[249],"show":[253],"that":[254],"predictor":[256],"large":[261],"measurement":[262],"mills":[273]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}