{"id":"https://openalex.org/W4388145375","doi":"https://doi.org/10.1109/tim.2023.3329156","title":"GNPENet: A Novel Convolutional Neural Network With Local Structure for Fault Diagnosis","display_name":"GNPENet: A Novel Convolutional Neural Network With Local Structure for Fault Diagnosis","publication_year":2023,"publication_date":"2023-11-01","ids":{"openalex":"https://openalex.org/W4388145375","doi":"https://doi.org/10.1109/tim.2023.3329156"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3329156","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3329156","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/A5100716987","display_name":"Jinping Wang","orcid":"https://orcid.org/0000-0002-3888-1742"},"institutions":[{"id":"https://openalex.org/I126924076","display_name":"Chongqing Normal University","ror":"https://ror.org/01dcw5w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I126924076"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinping Wang","raw_affiliation_strings":["College of Computer and Information Science, Chongqing Normal University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-3888-1742","affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Chongqing Normal University, Chongqing, China","institution_ids":["https://openalex.org/I126924076"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045657343","display_name":"Ruisheng Ran","orcid":"https://orcid.org/0000-0002-0785-2703"},"institutions":[{"id":"https://openalex.org/I126924076","display_name":"Chongqing Normal University","ror":"https://ror.org/01dcw5w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I126924076"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruisheng Ran","raw_affiliation_strings":["College of Computer and Information Science and the College of Intelligent Science, Chongqing Normal University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-0785-2703","affiliations":[{"raw_affiliation_string":"College of Computer and Information Science and the College of Intelligent Science, Chongqing Normal University, Chongqing, China","institution_ids":["https://openalex.org/I126924076"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046520540","display_name":"Bin Fang","orcid":"https://orcid.org/0000-0003-1955-6626"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Fang","raw_affiliation_strings":["College of Computer Science, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-1955-6626","affiliations":[{"raw_affiliation_string":"College of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6543,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.69510389,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"73","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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"}},{"id":"https://openalex.org/T13832","display_name":"Advanced Decision-Making Techniques","score":0.9476000070571899,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T14368","display_name":"Evaluation and Optimization Models","score":0.917900025844574,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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":0.7926805019378662},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6747777462005615},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5708799362182617},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.561665415763855},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5202051997184753},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5190178155899048},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5158935785293579},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4789060354232788},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.4489337205886841},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4282107651233673},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.41380631923675537},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37558993697166443},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36362504959106445},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17868739366531372}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7926805019378662},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6747777462005615},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5708799362182617},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.561665415763855},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5202051997184753},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5190178155899048},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5158935785293579},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4789060354232788},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4489337205886841},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4282107651233673},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.41380631923675537},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37558993697166443},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36362504959106445},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17868739366531372},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2023.3329156","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3329156","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":[{"score":0.6200000047683716,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G6139384048","display_name":null,"funder_award_id":"KJZD-K202100505","funder_id":"https://openalex.org/F4320324805","funder_display_name":"Chongqing Municipal Education Commission"}],"funders":[{"id":"https://openalex.org/F4320324805","display_name":"Chongqing Municipal Education Commission","ror":"https://ror.org/031nm5713"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W243674440","https://openalex.org/W1616262590","https://openalex.org/W1968266099","https://openalex.org/W2041785029","https://openalex.org/W2083955318","https://openalex.org/W2138451337","https://openalex.org/W2149414429","https://openalex.org/W2157427619","https://openalex.org/W2194775991","https://openalex.org/W2312559290","https://openalex.org/W2582337578","https://openalex.org/W2603304445","https://openalex.org/W2728505327","https://openalex.org/W2756130291","https://openalex.org/W2765317657","https://openalex.org/W2900367617","https://openalex.org/W2903312299","https://openalex.org/W2903948533","https://openalex.org/W2908984067","https://openalex.org/W2981258973","https://openalex.org/W2983088808","https://openalex.org/W2984457201","https://openalex.org/W3048718703","https://openalex.org/W3090238656","https://openalex.org/W3113432686","https://openalex.org/W3126794061","https://openalex.org/W3130100540","https://openalex.org/W3158668220","https://openalex.org/W3214066484","https://openalex.org/W4214493665","https://openalex.org/W4214935091","https://openalex.org/W4221019691","https://openalex.org/W4225147623","https://openalex.org/W4225942666","https://openalex.org/W4283800329","https://openalex.org/W4286564978","https://openalex.org/W4289868147","https://openalex.org/W4296965067","https://openalex.org/W4313122001","https://openalex.org/W4320343138","https://openalex.org/W4322707015","https://openalex.org/W4372260283","https://openalex.org/W4382584507","https://openalex.org/W4383066548","https://openalex.org/W6682644385","https://openalex.org/W6758731821"],"related_works":["https://openalex.org/W2579148721","https://openalex.org/W4387893611","https://openalex.org/W2347335694","https://openalex.org/W2091056927","https://openalex.org/W2067407580","https://openalex.org/W4317486777","https://openalex.org/W4389669152","https://openalex.org/W2038514069","https://openalex.org/W1967233468","https://openalex.org/W2009181529"],"abstract_inverted_index":{"With":[0],"the":[1,29,34,44,53,56,74,87,105,126,143,161],"development":[2],"of":[3,33,46,52,79,129,155],"modern":[4],"industry,":[5],"fault":[6,18,47,149],"diagnosis":[7,19,150],"has":[8,176],"become":[9],"an":[10],"important":[11],"research":[12],"field.":[13],"Currently,":[14],"many":[15],"methods":[16],"for":[17],"have":[20],"been":[21],"proposed.":[22],"As":[23],"a":[24,65,107,134],"method":[25,113],"designed":[26],"to":[27,99,124],"overcome":[28],"high":[30],"computational":[31],"complexity":[32],"convolutional":[35,127],"neural":[36],"network":[37],"(CNN),":[38],"PCANet":[39,54],"is":[40,55,64,117,122,140],"also":[41],"used":[42,123],"in":[43],"field":[45],"diagnosis.":[48],"The":[49,165],"core":[50],"algorithm":[51],"principal":[57],"component":[58],"analysis":[59],"(PCA)":[60],"algorithm.":[61],"However,":[62],"PCA":[63],"global":[66],"dimensionality":[67],"reduction":[68],"method,":[69],"which":[70],"cannot":[71],"effectively":[72],"analyze":[73],"local":[75,88,138],"spatial":[76],"geometry":[77],"structure":[78,89,139],"data":[80],"and":[81,101,120,158,180],"may":[82],"even":[83],"weaken":[84],"or":[85],"destroy":[86],"information.":[90],"Furthermore,":[91],"algorithms":[92],"based":[93,114],"on":[94,115,152],"L2-norm":[95],"are":[96],"very":[97],"sensitive":[98],"noise":[100],"outliers.":[102],"To":[103],"address":[104],"problems,":[106],"generalized":[108],"neighborhood":[109],"preserving":[110],"embedding":[111],"(GNPE)":[112],"Lp-norm":[116],"first":[118],"proposed,":[119,141],"it":[121],"learn":[125],"filters":[128],"CNN.":[130],"In":[131],"this":[132],"way,":[133],"novel":[135],"CNN":[136],"with":[137,171],"called":[142],"GNPE":[144],"Network":[145],"(GNPENet).":[146],"We":[147],"conduct":[148],"experiments":[151],"five":[153],"datasets":[154],"three":[156],"types":[157],"comprehensively":[159],"evaluate":[160],"proposed":[162],"GNPENet":[163,175],"method.":[164],"experimental":[166],"results":[167],"show":[168],"that,":[169],"compared":[170],"some":[172],"state-of-the-art":[173],"models,":[174],"better":[177],"feature":[178],"extraction":[179],"generalization":[181],"capabilities.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
