{"id":"https://openalex.org/W4414404924","doi":"https://doi.org/10.1109/tim.2025.3612627","title":"A CEEMDAN-CNN-BiLSTM-Based Method for Monitoring Wear Particles With Electrostatic Sensors","display_name":"A CEEMDAN-CNN-BiLSTM-Based Method for Monitoring Wear Particles With Electrostatic Sensors","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414404924","doi":"https://doi.org/10.1109/tim.2025.3612627"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2025.3612627","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2025.3612627","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/A5061166773","display_name":"Jing Cai","orcid":"https://orcid.org/0000-0001-5747-9399"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Cai","raw_affiliation_strings":["College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-5747-9399","affiliations":[{"raw_affiliation_string":"College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080008280","display_name":"Zhenglin Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenglin Wang","raw_affiliation_strings":["College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0009-9254-2694","affiliations":[{"raw_affiliation_string":"College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chong Cheng","orcid":"https://orcid.org/0009-0006-0015-647X"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chong Cheng","raw_affiliation_strings":["College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0006-0015-647X","affiliations":[{"raw_affiliation_string":"College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104334529","display_name":"Hangyuan Zhang","orcid":"https://orcid.org/0009-0003-4563-8390"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hangyuan Zhang","raw_affiliation_strings":["College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0003-4563-8390","affiliations":[{"raw_affiliation_string":"College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353892","display_name":"Xin Li","orcid":"https://orcid.org/0000-0002-5181-5870"},"institutions":[{"id":"https://openalex.org/I2799736854","display_name":"Nanjing Institute of Technology","ror":"https://ror.org/00n6txq60","country_code":"CN","type":"education","lineage":["https://openalex.org/I2799736854"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["School of Traffic Engineering, Nanjing Institute of Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-5181-5870","affiliations":[{"raw_affiliation_string":"School of Traffic Engineering, Nanjing Institute of Technology, Nanjing, China","institution_ids":["https://openalex.org/I2799736854"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yixin Zhang","orcid":"https://orcid.org/0009-0002-6794-843X"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixin Zhang","raw_affiliation_strings":["College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0002-6794-843X","affiliations":[{"raw_affiliation_string":"College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9253,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.77478407,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"74","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10461","display_name":"Gas Sensing Nanomaterials and Sensors","score":0.9442999958992004,"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"}},"topics":[{"id":"https://openalex.org/T10461","display_name":"Gas Sensing Nanomaterials and Sensors","score":0.9442999958992004,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9311000108718872,"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"}},{"id":"https://openalex.org/T12564","display_name":"Sensor Technology and Measurement Systems","score":0.9247000217437744,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6399999856948853},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5928999781608582},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.5663999915122986},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5302000045776367},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5145999789237976},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5116999745368958},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.510699987411499},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.4361000061035156},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.39489999413490295}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6399999856948853},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5928999781608582},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.5663999915122986},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5302000045776367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5221999883651733},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5145999789237976},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5116999745368958},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.510699987411499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5019000172615051},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.4361000061035156},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.39489999413490295},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.3808000087738037},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.35530000925064087},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.3531999886035919},{"id":"https://openalex.org/C100675267","wikidata":"https://www.wikidata.org/wiki/Q1371624","display_name":"Background noise","level":2,"score":0.3379000127315521},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.335099995136261},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.3237999975681305},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.31209999322891235},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C86781634","wikidata":"https://www.wikidata.org/wiki/Q2478325","display_name":"Environmental noise","level":3,"score":0.29319998621940613},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C137270730","wikidata":"https://www.wikidata.org/wiki/Q120811","display_name":"Detection theory","level":3,"score":0.28949999809265137},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.28540000319480896},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C205312793","wikidata":"https://www.wikidata.org/wiki/Q16002801","display_name":"Ambient noise level","level":3,"score":0.2702000141143799},{"id":"https://openalex.org/C184892835","wikidata":"https://www.wikidata.org/wiki/Q1474513","display_name":"Electromagnetic interference","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C117626034","wikidata":"https://www.wikidata.org/wiki/Q26336","display_name":"Electrostatics","level":2,"score":0.2556999921798706}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2025.3612627","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2025.3612627","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5881117195","display_name":null,"funder_award_id":"2024L042052001","funder_id":"https://openalex.org/F4320322857","funder_display_name":"Aeronautical Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320322857","display_name":"Aeronautical Science Foundation of China","ror":"https://ror.org/02wq41p38"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1968788953","https://openalex.org/W1995870330","https://openalex.org/W2003727424","https://openalex.org/W2024233812","https://openalex.org/W2049833369","https://openalex.org/W2254506961","https://openalex.org/W2369712355","https://openalex.org/W2753332519","https://openalex.org/W2889389601","https://openalex.org/W2903255379","https://openalex.org/W2904444186","https://openalex.org/W3007322587","https://openalex.org/W3094521302","https://openalex.org/W4312266138","https://openalex.org/W4387623770","https://openalex.org/W4389946659","https://openalex.org/W4392024736","https://openalex.org/W4393906084","https://openalex.org/W4399767819","https://openalex.org/W4399800519","https://openalex.org/W4400411536","https://openalex.org/W4401210483","https://openalex.org/W4402125007","https://openalex.org/W4403094629","https://openalex.org/W4406355103","https://openalex.org/W4407766010","https://openalex.org/W4409494226"],"related_works":[],"abstract_inverted_index":{"Electrostatic":[0],"sensors":[1],"play":[2],"a":[3,25,66,79,117,143],"crucial":[4],"role":[5],"in":[6,90,109],"wear":[7],"detection;":[8],"however,":[9],"they":[10],"are":[11],"highly":[12],"susceptible":[13],"to":[14,57,73,86],"environmental":[15],"interference.":[16],"To":[17,37],"address":[18,38],"signal":[19,95],"recognition":[20,34,107],"issues":[21],"under":[22,133],"such":[23,136],"conditions,":[24],"CEEMDAN-CNN-BiLSTM-based":[26],"method":[27,104],"for":[28],"oil":[29],"debris":[30],"electrostatic":[31],"sensor":[32],"particle":[33],"is":[35,71],"proposed.":[36],"noise":[39],"interference":[40],"and":[41,61,112,126,140],"improve":[42],"feature":[43],"extraction,":[44],"this":[45],"study":[46],"uses":[47],"Complete":[48],"Ensemble":[49],"Empirical":[50],"Mode":[51],"Decomposition":[52],"with":[53,78,142],"Adaptive":[54],"Noise":[55],"(CEEMDAN)":[56],"reduce":[58],"mode":[59],"mixing":[60],"enhance":[62],"target":[63],"signals.":[64],"Subsequently,":[65],"Convolutional":[67],"Neural":[68],"Network":[69,84],"(CNN)":[70],"used":[72],"extract":[74],"local":[75],"features,":[76],"combined":[77],"Bidirectional":[80],"Long":[81],"Short-Term":[82],"Memory":[83],"(BiLSTM)":[85],"capture":[87],"long-term":[88],"dependencies":[89],"time":[91],"series,":[92],"thereby":[93],"improving":[94],"classification":[96,118,144],"accuracy.":[97],"Experimental":[98],"results":[99],"indicate":[100],"that":[101],"the":[102],"CEEMDAN-CNN-BiLSTM":[103],"exhibits":[105],"superior":[106],"capabilities":[108],"both":[110],"simulated":[111],"real":[113],"experimental":[114],"data,":[115],"achieving":[116],"accuracy":[119,145],"of":[120,146],"99.1%,":[121],"surpassing":[122],"methods":[123],"like":[124],"EMD-CNN-LSTM":[125],"CEEMDAN-CNN-LSTM.":[127],"Moreover,":[128],"it":[129],"maintains":[130],"strong":[131],"robustness":[132],"challenging":[134],"conditions":[135],"as":[137],"high":[138],"temperatures":[139],"vibrations,":[141],"98.3%.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}