{"id":"https://openalex.org/W4313229372","doi":"https://doi.org/10.1109/tnnls.2022.3230458","title":"Explainable Graph Wavelet Denoising Network for Intelligent Fault Diagnosis","display_name":"Explainable Graph Wavelet Denoising Network for Intelligent Fault Diagnosis","publication_year":2022,"publication_date":"2022-12-28","ids":{"openalex":"https://openalex.org/W4313229372","doi":"https://doi.org/10.1109/tnnls.2022.3230458","pmid":"https://pubmed.ncbi.nlm.nih.gov/37015709"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3230458","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3230458","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5000345697","display_name":"Tianfu Li","orcid":"https://orcid.org/0000-0003-4388-9578"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tianfu Li","raw_affiliation_strings":["School of Mechanical Engineering, Xi&#x2019;an Jiaotong University, Shaanxi, Xi\u2019an, China"],"raw_orcid":"https://orcid.org/0000-0003-4388-9578","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xi&#x2019;an Jiaotong University, Shaanxi, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027894205","display_name":"Chuang Sun","orcid":"https://orcid.org/0000-0001-6616-3791"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuang Sun","raw_affiliation_strings":["School of Mechanical Engineering, Xi&#x2019;an Jiaotong University, Shaanxi, Xi\u2019an, China"],"raw_orcid":"https://orcid.org/0000-0001-6616-3791","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xi&#x2019;an Jiaotong University, Shaanxi, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005442338","display_name":"Sinan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sinan Li","raw_affiliation_strings":["School of Mechanical Engineering, Xi&#x2019;an Jiaotong University, Shaanxi, Xi\u2019an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xi&#x2019;an Jiaotong University, Shaanxi, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115592264","display_name":"Zhiying Wang","orcid":"https://orcid.org/0009-0001-7064-6419"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiying Wang","raw_affiliation_strings":["School of Mechanical Engineering, Xi&#x2019;an Jiaotong University, Shaanxi, Xi\u2019an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xi&#x2019;an Jiaotong University, Shaanxi, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100779843","display_name":"Xuefeng Chen","orcid":"https://orcid.org/0000-0002-0130-3172"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuefeng Chen","raw_affiliation_strings":["School of Mechanical Engineering, Xi&#x2019;an Jiaotong University, Shaanxi, Xi\u2019an, China"],"raw_orcid":"https://orcid.org/0000-0002-0130-3172","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xi&#x2019;an Jiaotong University, Shaanxi, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011148961","display_name":"Ruqiang Yan","orcid":"https://orcid.org/0000-0002-1250-4084"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruqiang Yan","raw_affiliation_strings":["School of Mechanical Engineering, Xi&#x2019;an Jiaotong University, Shaanxi, Xi\u2019an, China"],"raw_orcid":"https://orcid.org/0000-0002-1250-4084","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xi&#x2019;an Jiaotong University, Shaanxi, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5000345697"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":10.6926,"has_fulltext":false,"cited_by_count":97,"citation_normalized_percentile":{"value":0.99083185,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"35","issue":"6","first_page":"8535","last_page":"8548"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9925000071525574,"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"}},"topics":[{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9925000071525574,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9527999758720398,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.9460999965667725,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6790562868118286},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6727687120437622},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6516952514648438},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.601506233215332},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5894613265991211},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.545062243938446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5376869440078735},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5315133333206177},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.413994163274765},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3489590287208557},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32925671339035034},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1182381808757782}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6790562868118286},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6727687120437622},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6516952514648438},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.601506233215332},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5894613265991211},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.545062243938446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5376869440078735},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5315133333206177},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.413994163274765},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3489590287208557},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32925671339035034},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1182381808757782},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3230458","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3230458","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37015709","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37015709","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":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1303901245","display_name":null,"funder_award_id":"52175116","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6644378097","display_name":null,"funder_award_id":"92060302","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"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W196071634","https://openalex.org/W1662382123","https://openalex.org/W2060304859","https://openalex.org/W2132294263","https://openalex.org/W2318004685","https://openalex.org/W2558748708","https://openalex.org/W2736225434","https://openalex.org/W2761148314","https://openalex.org/W2768753204","https://openalex.org/W2789811186","https://openalex.org/W2899379687","https://openalex.org/W2907492528","https://openalex.org/W2914953695","https://openalex.org/W2942682738","https://openalex.org/W2943549535","https://openalex.org/W2946048316","https://openalex.org/W2950898568","https://openalex.org/W2962711740","https://openalex.org/W2962810718","https://openalex.org/W2963573361","https://openalex.org/W2964015378","https://openalex.org/W2977117446","https://openalex.org/W2997417149","https://openalex.org/W3000384844","https://openalex.org/W3005676037","https://openalex.org/W3011667710","https://openalex.org/W3021048621","https://openalex.org/W3033847194","https://openalex.org/W3039216919","https://openalex.org/W3041076719","https://openalex.org/W3098742616","https://openalex.org/W3110510730","https://openalex.org/W3111706174","https://openalex.org/W3111965349","https://openalex.org/W3121022549","https://openalex.org/W3122347867","https://openalex.org/W3126441351","https://openalex.org/W3134164546","https://openalex.org/W3135695944","https://openalex.org/W3155371252","https://openalex.org/W3157039246","https://openalex.org/W3157123770","https://openalex.org/W3160541836","https://openalex.org/W3168684497","https://openalex.org/W3174482241","https://openalex.org/W3176074827","https://openalex.org/W3178034484","https://openalex.org/W3179111421","https://openalex.org/W3200496415","https://openalex.org/W3208157985","https://openalex.org/W3213159297","https://openalex.org/W4200473862","https://openalex.org/W4206612301","https://openalex.org/W4285248638","https://openalex.org/W4286681770","https://openalex.org/W4297733535","https://openalex.org/W6637178625","https://openalex.org/W6690815549","https://openalex.org/W6726873649","https://openalex.org/W6736685754","https://openalex.org/W6738964360","https://openalex.org/W6754929296","https://openalex.org/W6756192570","https://openalex.org/W6760001035","https://openalex.org/W6761665040","https://openalex.org/W6786906566","https://openalex.org/W7025035218"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4361193272","https://openalex.org/W2963326959","https://openalex.org/W4388685194","https://openalex.org/W4312407344","https://openalex.org/W2894289927"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"(DL)-based":[2],"intelligent":[3,45,111],"fault":[4,16,112],"diagnosis":[5,17,46,113],"methods":[6,47],"have":[7],"greatly":[8],"promoted":[9],"the":[10,13,37,59,76,84,94,123,134,139,149,175,178,182,193,199,205,217,221],"development":[11],"of":[12,15,32,177,208,220],"field":[14],"due":[18],"to":[19,80,109,132,157,173,203],"their":[20,81,91],"powerful":[21],"feature":[22,160],"extraction":[23,161],"ability":[24],"for":[25,162],"handling":[26],"massive":[27],"monitoring":[28],"data.":[29],"However,":[30],"most":[31],"them":[33],"still":[34],"suffer":[35],"from":[36,53,75],"following":[38],"three":[39],"limitations.":[40],"First,":[41],"many":[42],"existing":[43],"DL-based":[44],"cannot":[48],"extract":[49],"proper":[50],"discriminative":[51],"features":[52,74,86,207],"signals":[54,64,125],"with":[55],"strong":[56],"noise.":[57],"Second,":[58],"interactions":[60,135],"or":[61],"relationships":[62],"between":[63],"are":[65,126,171],"ignored,":[66],"while":[67],"they":[68],"mainly":[69],"focus":[70],"on":[71,148],"extracting":[72],"temporal":[73],"signal.":[77],"Third,":[78],"owing":[79],"black-box":[82],"nature,":[83],"learned":[85],"lack":[87],"interpretability,":[88],"which":[89,154,227],"hinders":[90],"application":[92],"in":[93,118],"industry.":[95],"To":[96],"tackle":[97],"these":[98],"issues,":[99],"an":[100],"explainable":[101],"graph":[102,140,151],"wavelet":[103,141,152],"denoising":[104,142],"network":[105],"(GWDN)":[106],"is":[107,145,232],"proposed":[108,146,179],"achieve":[110,158,189],"under":[114],"noisy":[115],"working":[116],"conditions":[117],"this":[119],"article.":[120],"In":[121],"GWDN,":[122,180],"collected":[124],"first":[127],"transformed":[128],"into":[129],"graph-structured":[130,163],"data":[131,164],"consider":[133],"among":[136,192],"signals.":[137],"Then,":[138],"convolution":[143],"(GWDConv)":[144],"based":[147],"discrete":[150],"frame,":[153],"allows":[155],"GWDN":[156,187,231],"multiscale":[159],"and":[165,181,223],"realize":[166,224],"signal":[167,222,225],"denoising.":[168],"Extensive":[169],"experiments":[170],"implemented":[172],"verify":[174],"efficacy":[176],"experimental":[183],"results":[184],"show":[185],"that":[186,212,230],"can":[188,214],"state-of-the-art":[190],"performance":[191],"comparison":[194],"methods.":[195],"Besides,":[196],"by":[197],"using":[198],"square":[200],"envelope":[201],"spectrum":[202],"analyze":[204],"extracted":[206],"GWDConv,":[209],"we":[210],"find":[211],"it":[213],"well":[215],"retain":[216],"fault-related":[218],"components":[219],"denoising,":[226],"further":[228],"proves":[229],"explainable.":[233]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":42},{"year":2024,"cited_by_count":25},{"year":2023,"cited_by_count":21}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
