{"id":"https://openalex.org/W4396232140","doi":"https://doi.org/10.1145/3641343.3641355","title":"Research on Sensor Anomaly Signal Processing Method Based on Convolutional Neural Network","display_name":"Research on Sensor Anomaly Signal Processing Method Based on Convolutional Neural Network","publication_year":2023,"publication_date":"2023-12-08","ids":{"openalex":"https://openalex.org/W4396232140","doi":"https://doi.org/10.1145/3641343.3641355"},"language":"en","primary_location":{"id":"doi:10.1145/3641343.3641355","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3641343.3641355","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 3rd International Conference on Electronic Information Technology and Smart Agriculture","raw_type":"proceedings-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/A5103006969","display_name":"Yufeng Zhang","orcid":"https://orcid.org/0009-0002-5379-2622"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Yufeng Zhang","raw_affiliation_strings":["Imperial College London, British"],"affiliations":[{"raw_affiliation_string":"Imperial College London, British","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5103006969"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2207442,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"68","last_page":"74"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994000196456909,"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":0.9994000196456909,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9606000185012817,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9560999870300293,"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":0.7149624228477478},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7107506394386292},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.5495773553848267},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.515910267829895},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.502844512462616},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4947457015514374},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.47297564148902893},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4650940001010895},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4433841109275818},{"id":"https://openalex.org/keywords/radar-signal-processing","display_name":"Radar signal processing","score":0.4427052140235901},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.19923663139343262},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.06354814767837524},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.05911970138549805}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7149624228477478},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7107506394386292},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.5495773553848267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.515910267829895},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.502844512462616},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4947457015514374},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.47297564148902893},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4650940001010895},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4433841109275818},{"id":"https://openalex.org/C2987759513","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar signal processing","level":4,"score":0.4427052140235901},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.19923663139343262},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.06354814767837524},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.05911970138549805},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3641343.3641355","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3641343.3641355","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 3rd International Conference on Electronic Information Technology and Smart Agriculture","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2965318968","https://openalex.org/W2965846681","https://openalex.org/W2968368194","https://openalex.org/W2976991873","https://openalex.org/W3082712634","https://openalex.org/W3094627074","https://openalex.org/W3119698209","https://openalex.org/W3137494282","https://openalex.org/W3161550624","https://openalex.org/W3183477965","https://openalex.org/W3190748826","https://openalex.org/W3208598990"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4377864969","https://openalex.org/W2972971679"],"abstract_inverted_index":{"The":[0,80],"aim":[1],"of":[2,27,42,77,82,105,166,173],"this":[3,134,167],"study":[4,135],"is":[5,70],"to":[6,20,101,162],"investigate":[7],"Convolutional":[8],"Neural":[9],"Network":[10],"(CNN)-based":[11],"anomaly":[12,116,128,142],"signal":[13,117,129],"processing":[14,69,118,130],"methods":[15,57],"for":[16,140],"sensors":[17],"in":[18,30,47,51,73,114,133,147,169],"order":[19],"improve":[21],"the":[22,36,75,87,125,156,164],"detection":[23,143],"and":[24,40,44,61,95,122,144,160],"prediction":[25,98,145],"performance":[26,99,146],"anomalous":[28],"data":[29],"complex":[31,49],"industrial":[32,148],"environments.":[33],"We":[34],"analyse":[35],"nonlinear":[37,78],"descriptive":[38],"ability":[39],"adaptability":[41,121],"CNNs":[43],"their":[45],"advantages":[46],"capturing":[48],"correlations":[50],"sensor":[52,115,127],"signals.":[53],"By":[54],"comparing":[55],"traditional":[56],"with":[58,119],"neural":[59,157],"networks":[60],"fuzzy":[62],"identification":[63],"methods,":[64],"we":[65],"find":[66],"that":[67,86,110],"CNN-based":[68,88,126],"more":[71,96],"advantageous":[72],"modelling":[74],"dynamics":[76],"systems.":[79,150],"results":[81],"simulation":[83],"experiments":[84],"show":[85],"method":[89,131,168],"has":[90],"a":[91,170],"smaller":[92],"average":[93],"error":[94],"stable":[97],"compared":[100],"other":[102],"methods.":[103],"Comparison":[104],"different":[106],"network":[107,158],"structures":[108],"shows":[109],"CNN":[111],"performs":[112],"well":[113],"better":[120],"generalisation.":[123],"Overall,":[124],"proposed":[132],"provides":[136],"an":[137],"effective":[138],"solution":[139],"improving":[141],"automation":[149],"Future":[151],"research":[152],"can":[153],"further":[154],"optimise":[155],"structure":[159],"parameters":[161],"promote":[163],"application":[165],"wider":[171],"range":[172],"fields.":[174]},"counts_by_year":[],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}
