{"id":"https://openalex.org/W4388407789","doi":"https://doi.org/10.1109/tim.2023.3330221","title":"Mass Flow Rate Measurement of Pneumatically Conveyed Solids in a Square-Shaped Pipe Through Multisensor Fusion and Data-Driven Modeling","display_name":"Mass Flow Rate Measurement of Pneumatically Conveyed Solids in a Square-Shaped Pipe Through Multisensor Fusion and Data-Driven Modeling","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4388407789","doi":"https://doi.org/10.1109/tim.2023.3330221"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3330221","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3330221","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","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/A5052420980","display_name":"Xingxing Zeng","orcid":"https://orcid.org/0000-0001-8337-067X"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingxing Zeng","raw_affiliation_strings":["School of Control and Computer Engineering, North China Electric Power University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8337-067X","affiliations":[{"raw_affiliation_string":"School of Control and Computer Engineering, North China Electric Power University, Beijing, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078729695","display_name":"Yong Yan","orcid":"https://orcid.org/0000-0001-7135-5456"},"institutions":[{"id":"https://openalex.org/I20581793","display_name":"University of Kent","ror":"https://ror.org/00xkeyj56","country_code":"GB","type":"education","lineage":["https://openalex.org/I20581793"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yong Yan","raw_affiliation_strings":["School of Engineering, University of Kent, Canterbury, Kent, U.K"],"raw_orcid":"https://orcid.org/0000-0001-7135-5456","affiliations":[{"raw_affiliation_string":"School of Engineering, University of Kent, Canterbury, Kent, U.K","institution_ids":["https://openalex.org/I20581793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070671007","display_name":"Xiangchen Qian","orcid":"https://orcid.org/0000-0002-9070-994X"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangchen Qian","raw_affiliation_strings":["School of Control and Computer Engineering, North China Electric Power University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9070-994X","affiliations":[{"raw_affiliation_string":"School of Control and Computer Engineering, North China Electric Power University, Beijing, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070435655","display_name":"Yongyue Wang","orcid":"https://orcid.org/0000-0002-8370-9597"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongyue Wang","raw_affiliation_strings":["School of Control and Computer Engineering, North China Electric Power University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8370-9597","affiliations":[{"raw_affiliation_string":"School of Control and Computer Engineering, North China Electric Power University, Beijing, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103169171","display_name":"Jie Zhang","orcid":"https://orcid.org/0009-0000-9266-2092"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Zhang","raw_affiliation_strings":["School of Control and Computer Engineering, North China Electric Power University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0000-9266-2092","affiliations":[{"raw_affiliation_string":"School of Control and Computer Engineering, North China Electric Power University, Beijing, China","institution_ids":["https://openalex.org/I153473198"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.7509,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.98946411,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"72","issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12537","display_name":"Flow Measurement and Analysis","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T12537","display_name":"Flow Measurement and Analysis","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T11220","display_name":"Water Systems and Optimization","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9983000159263611,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mass-flow-rate","display_name":"Mass flow rate","score":0.602139949798584},{"id":"https://openalex.org/keywords/volumetric-flow-rate","display_name":"Volumetric flow rate","score":0.5309808850288391},{"id":"https://openalex.org/keywords/pressure-sensor","display_name":"Pressure sensor","score":0.49483388662338257},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47089579701423645},{"id":"https://openalex.org/keywords/capacitive-sensing","display_name":"Capacitive sensing","score":0.46865907311439514},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.465833842754364},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.45595669746398926},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.45445892214775085},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4453596770763397},{"id":"https://openalex.org/keywords/mass-flow","display_name":"Mass flow","score":0.43125271797180176},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.394106924533844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34360387921333313},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.30000004172325134},{"id":"https://openalex.org/keywords/mechanics","display_name":"Mechanics","score":0.2545742988586426},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.23456841707229614},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.13736510276794434},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.12067043781280518},{"id":"https://openalex.org/keywords/aerospace-engineering","display_name":"Aerospace engineering","score":0.12027302384376526},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11900869011878967},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.11584120988845825},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09544309973716736}],"concepts":[{"id":"https://openalex.org/C75892298","wikidata":"https://www.wikidata.org/wiki/Q1366187","display_name":"Mass flow rate","level":2,"score":0.602139949798584},{"id":"https://openalex.org/C172120300","wikidata":"https://www.wikidata.org/wiki/Q1134348","display_name":"Volumetric flow rate","level":2,"score":0.5309808850288391},{"id":"https://openalex.org/C41325743","wikidata":"https://www.wikidata.org/wiki/Q1261040","display_name":"Pressure sensor","level":2,"score":0.49483388662338257},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47089579701423645},{"id":"https://openalex.org/C206755178","wikidata":"https://www.wikidata.org/wiki/Q1131271","display_name":"Capacitive sensing","level":2,"score":0.46865907311439514},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.465833842754364},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.45595669746398926},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.45445892214775085},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4453596770763397},{"id":"https://openalex.org/C33493971","wikidata":"https://www.wikidata.org/wiki/Q3295893","display_name":"Mass flow","level":2,"score":0.43125271797180176},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.394106924533844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34360387921333313},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.30000004172325134},{"id":"https://openalex.org/C57879066","wikidata":"https://www.wikidata.org/wiki/Q41217","display_name":"Mechanics","level":1,"score":0.2545742988586426},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.23456841707229614},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.13736510276794434},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12067043781280518},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.12027302384376526},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11900869011878967},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.11584120988845825},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09544309973716736}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tim.2023.3330221","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3330221","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},{"id":"pmh:oai:kar.kent.ac.uk:103444","is_oa":false,"landing_page_url":"https://kar.kent.ac.uk/103444/1/TIM-23-04980_Mass%20Flow%20Rate%20Measurement_Manuscript.doc","pdf_url":null,"source":{"id":"https://openalex.org/S4377196264","display_name":"Kent Academic Repository (University of Kent)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I20581793","host_organization_name":"University of Kent","host_organization_lineage":["https://openalex.org/I20581793"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G2529702924","display_name":null,"funder_award_id":"62273143","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1192033379","https://openalex.org/W1963436953","https://openalex.org/W1974831921","https://openalex.org/W2004762910","https://openalex.org/W2028606280","https://openalex.org/W2042998857","https://openalex.org/W2091076221","https://openalex.org/W2101924850","https://openalex.org/W2225591460","https://openalex.org/W2329919683","https://openalex.org/W2516485688","https://openalex.org/W2530777692","https://openalex.org/W2563842307","https://openalex.org/W2579897446","https://openalex.org/W2608088778","https://openalex.org/W2800811541","https://openalex.org/W2887547880","https://openalex.org/W2901856993","https://openalex.org/W2916254414","https://openalex.org/W2971952876","https://openalex.org/W2979941693","https://openalex.org/W3082459645","https://openalex.org/W3087363114","https://openalex.org/W3089318091","https://openalex.org/W3190877381","https://openalex.org/W3203556327","https://openalex.org/W4214653023","https://openalex.org/W4280623724","https://openalex.org/W4290647841","https://openalex.org/W4310204380","https://openalex.org/W4313855387"],"related_works":["https://openalex.org/W3015749751","https://openalex.org/W4387713458","https://openalex.org/W2372430764","https://openalex.org/W4311325650","https://openalex.org/W1979670679","https://openalex.org/W4318066946","https://openalex.org/W2980663142","https://openalex.org/W4226072595","https://openalex.org/W769946470","https://openalex.org/W2169474132"],"abstract_inverted_index":{"Online":[0],"continuous":[1],"measurement":[2],"of":[3,8,31,41,44,47,50,59,103,112,135,140,150,184,232],"the":[4,37,45,48,55,94,99,133,136,185,215,228],"mass":[5,38,137,229],"flow":[6,39,52,138,230],"rate":[7,40,139,231],"pneumatically":[9],"conveyed":[10],"solids":[11,42,51,106,145,219,233],"in":[12,35,98],"a":[13,28,60,66,110,156,164,202,247],"square-shaped":[14,61],"pipe":[15],"is":[16,88,115,175,180],"desirable":[17],"for":[18],"monitoring":[19],"and":[20,69,84,90,105,121,147,169,177,194,208,213,227],"optimizing":[21],"industrial":[22],"processes.":[23],"However,":[24],"existing":[25],"techniques":[26],"using":[27],"single":[29],"type":[30],"sensor":[32,127],"have":[33],"limitations":[34],"measuring":[36],"because":[43],"complexity":[46],"dynamics":[49],"due":[53],"to":[54,73,92,211,224,236],"four":[56],"sharp":[57],"corners":[58],"pipe.":[62],"This":[63],"paper":[64],"proposes":[65],"multi-sensor":[67,78],"fusion":[68],"data-driven":[70,157,160],"modelling-based":[71],"method":[72],"tackle":[74],"this":[75],"challenge.":[76],"A":[77,159],"system":[79],"based":[80,162],"on":[81,125,163,201,205],"acoustic,":[82],"capacitive,":[83],"electrostatic":[85],"sensing":[86],"principles":[87],"designed":[89],"implemented":[91],"obtain":[93],"sound":[95],"pressure":[96],"level":[97],"flow,":[100],"volumetric":[101],"concentration":[102,149],"solids,":[104,141,151],"velocity,":[107],"respectively.":[108],"Simultaneously,":[109],"range":[111],"statistical":[113,130],"features":[114,131],"obtained":[116],"by":[117],"performing":[118],"time-domain,":[119],"frequency-domain,":[120],"time-frequency":[122],"domain":[123],"analyses":[124],"all":[126,243,253],"signals.":[128],"The":[129,239],"reflecting":[132],"variation":[134],"as":[142,144],"well":[143],"velocity":[146,220],"volume":[148],"are":[152],"then":[153],"fed":[154],"into":[155],"model.":[158],"model":[161,217,241],"combined":[165],"convolutional":[166],"neural":[167,188],"network":[168,174],"long":[170],"short-term":[171],"memory":[172],"(CNN-LSTM)":[173],"established,":[176],"its":[178],"performance":[179],"compared":[181],"with":[182,218,246],"those":[183],"back-propagation":[186],"artificial":[187],"network,":[189],"support":[190],"vector":[191],"machine,":[192],"CNN,":[193],"LSTM":[195],"models.":[196],"Experimental":[197],"tests":[198],"were":[199],"conducted":[200],"laboratory-scale":[203],"rig":[204],"both":[206],"horizontal":[207],"vertical":[209],"pipelines":[210],"train":[212],"evaluate":[214],"CNN-LSTM":[216,240],"ranging":[221],"from":[222,234],"11":[223],"23":[225],"m/s":[226],"8":[235],"26":[237],"kg/h.":[238],"outperforms":[242],"other":[244],"models":[245],"relative":[248],"error":[249],"within":[250],"\u00b11%":[251],"under":[252],"test":[254],"conditions.":[255]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":22},{"year":2023,"cited_by_count":4}],"updated_date":"2026-07-09T07:52:08.696243","created_date":"2023-11-07T00:00:00"}
