{"id":"https://openalex.org/W4376645472","doi":"https://doi.org/10.3390/s23104781","title":"Convolutional Neural Network-Based Transformer Fault Diagnosis Using Vibration Signals","display_name":"Convolutional Neural Network-Based Transformer Fault Diagnosis Using Vibration Signals","publication_year":2023,"publication_date":"2023-05-16","ids":{"openalex":"https://openalex.org/W4376645472","doi":"https://doi.org/10.3390/s23104781","pmid":"https://pubmed.ncbi.nlm.nih.gov/37430695"},"language":"en","primary_location":{"id":"doi:10.3390/s23104781","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23104781","pdf_url":"https://www.mdpi.com/1424-8220/23/10/4781/pdf?version=1684216388","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/10/4781/pdf?version=1684216388","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100323225","display_name":"Chao Li","orcid":"https://orcid.org/0000-0002-7686-6922"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Li","raw_affiliation_strings":["School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China"],"raw_orcid":"https://orcid.org/0000-0002-7686-6922","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100640365","display_name":"Jie Chen","orcid":"https://orcid.org/0000-0001-9259-8270"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Chen","raw_affiliation_strings":["School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China"],"raw_orcid":"https://orcid.org/0000-0001-9259-8270","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018488940","display_name":"Cheng Yang","orcid":"https://orcid.org/0000-0002-4654-5861"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng Yang","raw_affiliation_strings":["China Institute of Marine Technology and Economy, Beijing 100081, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Institute of Marine Technology and Economy, Beijing 100081, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057439257","display_name":"Jingjian Yang","orcid":"https://orcid.org/0000-0002-1577-2500"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingjian Yang","raw_affiliation_strings":["School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101446013","display_name":"Zhigang Liu","orcid":"https://orcid.org/0000-0003-3054-1425"},"institutions":[{"id":"https://openalex.org/I4210118977","display_name":"Shanghai Tunnel Engineering Rail Transit Design & Research Institute","ror":"https://ror.org/02zznv955","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118977"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigang Liu","raw_affiliation_strings":["Beijing Rail Transit Electrical Engineering Technology Research Center, Beijing 100044, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Rail Transit Electrical Engineering Technology Research Center, Beijing 100044, China","institution_ids":["https://openalex.org/I4210118977"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046138738","display_name":"Pooya Davari","orcid":"https://orcid.org/0000-0002-3273-3271"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Pooya Davari","raw_affiliation_strings":["AAU Energy, Aalborg University, 9220 Aalborg, Denmark"],"raw_orcid":"https://orcid.org/0000-0002-3273-3271","affiliations":[{"raw_affiliation_string":"AAU Energy, Aalborg University, 9220 Aalborg, Denmark","institution_ids":["https://openalex.org/I891191580"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046138738","https://openalex.org/A5100640365"],"corresponding_institution_ids":["https://openalex.org/I21193070","https://openalex.org/I891191580"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":3.7863,"has_fulltext":true,"cited_by_count":45,"citation_normalized_percentile":{"value":0.94650305,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"23","issue":"10","first_page":"4781","last_page":"4781"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11343","display_name":"Power Transformer Diagnostics and Insulation","score":0.9998999834060669,"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/T11343","display_name":"Power Transformer Diagnostics and Insulation","score":0.9998999834060669,"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/T10511","display_name":"High voltage insulation and dielectric phenomena","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9857000112533569,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6751580834388733},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6749443411827087},{"id":"https://openalex.org/keywords/vibration","display_name":"Vibration","score":0.58717280626297},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5814859867095947},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5709465742111206},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.565155565738678},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5168114900588989},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4892682731151581},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4681071937084198},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4520249366760254},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.4439782500267029},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.35524675250053406},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.12604674696922302},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.07961893081665039}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6751580834388733},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6749443411827087},{"id":"https://openalex.org/C198394728","wikidata":"https://www.wikidata.org/wiki/Q3695508","display_name":"Vibration","level":2,"score":0.58717280626297},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5814859867095947},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5709465742111206},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.565155565738678},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5168114900588989},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4892682731151581},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4681071937084198},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4520249366760254},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.4439782500267029},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.35524675250053406},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.12604674696922302},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.07961893081665039},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.3390/s23104781","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23104781","pdf_url":"https://www.mdpi.com/1424-8220/23/10/4781/pdf?version=1684216388","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:37430695","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37430695","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10223529","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10223529","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10223529/pdf/sensors-23-04781.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:pure.atira.dk:publications/61361b10-8061-46b5-b891-b876324f1b2b","is_oa":true,"landing_page_url":"https://vbn.aau.dk/da/publications/61361b10-8061-46b5-b891-b876324f1b2b","pdf_url":"https://vbn.aau.dk/ws/files/528973227/sensors_23_04781.pdf","source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Li , C , Chen , J , Yang , C , Yang , J , Liu , Z &amp; Davari , P 2023 , ' Convolutional Neural Network-Based Transformer Fault Diagnosis Using Vibration Signals ' , Sensors , vol. 23 , no. 10 , 4781 . https://doi.org/10.3390/s23104781","raw_type":"article"},{"id":"pmh:oai:doaj.org/article:47cc267d313d46c496029bc433e94a94","is_oa":true,"landing_page_url":"https://doaj.org/article/47cc267d313d46c496029bc433e94a94","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":"Sensors, Vol 23, Iss 10, p 4781 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/23/10/4781/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s23104781","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 23; Issue 10; Pages: 4781","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s23104781","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23104781","pdf_url":"https://www.mdpi.com/1424-8220/23/10/4781/pdf?version=1684216388","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2923021617","display_name":null,"funder_award_id":"2018JBZ004","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4376645472.pdf"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W2003205626","https://openalex.org/W2140417752","https://openalex.org/W2258884143","https://openalex.org/W2302255633","https://openalex.org/W2564096887","https://openalex.org/W2790391631","https://openalex.org/W2792745021","https://openalex.org/W2794042936","https://openalex.org/W2883139641","https://openalex.org/W2890120821","https://openalex.org/W2897953250","https://openalex.org/W2899893835","https://openalex.org/W2907007702","https://openalex.org/W2946948417","https://openalex.org/W2950438065","https://openalex.org/W2951660826","https://openalex.org/W2954948187","https://openalex.org/W2998589268","https://openalex.org/W3002188287","https://openalex.org/W3011435659","https://openalex.org/W3017520968","https://openalex.org/W3019295470","https://openalex.org/W3019762726","https://openalex.org/W3041518653","https://openalex.org/W3089140114","https://openalex.org/W3093956116","https://openalex.org/W3110362286","https://openalex.org/W3113181398","https://openalex.org/W3127258696","https://openalex.org/W3134028555","https://openalex.org/W3134472053","https://openalex.org/W3157154930","https://openalex.org/W3163693889","https://openalex.org/W3165652178","https://openalex.org/W3168997536","https://openalex.org/W3169118609","https://openalex.org/W3188402091","https://openalex.org/W3192807145","https://openalex.org/W3196446608","https://openalex.org/W3199865215","https://openalex.org/W6764195225","https://openalex.org/W6799372580","https://openalex.org/W6801018465"],"related_works":["https://openalex.org/W4390421286","https://openalex.org/W4280563792","https://openalex.org/W2140186469","https://openalex.org/W4389724018","https://openalex.org/W4318719684","https://openalex.org/W2775233965","https://openalex.org/W4206951940","https://openalex.org/W4293868382","https://openalex.org/W4382602594","https://openalex.org/W4387850423"],"abstract_inverted_index":{"Fast":[0],"and":[1,10,29,37,69,136,142,146],"accurate":[2],"fault":[3,17,52,79,127],"diagnosis":[4,18,53,157],"is":[5,19,63,91,117,134,166],"crucial":[6],"to":[7,24,65,101,119,168],"transformer":[8,16,126],"safety":[9],"cost-effectiveness.":[11],"Recently,":[12],"vibration":[13,58,73,84,99],"analysis":[14],"for":[15,51,93],"attracting":[20],"increasing":[21],"attention":[22],"due":[23],"its":[25,143],"ease":[26],"of":[27,39,54,125,163],"implementation":[28],"low":[30],"cost,":[31],"while":[32],"the":[33,71,78,83,86,106,121,130,139,154],"complex":[34],"operating":[35],"environment":[36],"loads":[38],"transformers":[40,56],"also":[41],"pose":[42],"challenges.":[43],"This":[44],"study":[45],"proposed":[46,118,131,155],"a":[47],"novel":[48],"deep-learning-enabled":[49],"method":[50,158],"dry-type":[55],"using":[57],"signals.":[59,74],"An":[60],"experimental":[61],"setup":[62],"designed":[64],"simulate":[66],"different":[67],"faults":[68],"collect":[70],"corresponding":[72],"To":[75],"find":[76],"out":[77],"information":[80],"hidden":[81],"in":[82],"signals,":[85],"continuous":[87],"wavelet":[88],"transform":[89],"(CWT)":[90],"applied":[92],"feature":[94],"extraction,":[95],"which":[96,165],"can":[97],"convert":[98],"signals":[100],"red-green-blue":[102],"(RGB)":[103],"images":[104],"with":[105,138],"time-frequency":[107],"relationship.":[108],"Then,":[109],"an":[110,160],"improved":[111],"convolutional":[112],"neural":[113],"network":[114],"(CNN)":[115],"model":[116,133],"complete":[120],"image":[122],"recognition":[123],"task":[124],"diagnosis.":[128],"Finally,":[129],"CNN":[132],"trained":[135],"tested":[137],"collected":[140],"data,":[141],"optimal":[144],"structure":[145],"hyperparameters":[147],"are":[148],"determined.":[149],"The":[150],"results":[151],"show":[152],"that":[153],"intelligent":[156],"achieves":[159],"overall":[161],"accuracy":[162],"99.95%,":[164],"superior":[167],"other":[169],"compared":[170],"machine":[171],"learning":[172],"methods.":[173]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":22},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-10-10T00:00:00"}
