{"id":"https://openalex.org/W2943389092","doi":"https://doi.org/10.1109/tie.2019.2912763","title":"Data-Driven Fault Diagnosis Method Based on Compressed Sensing and Improved Multiscale Network","display_name":"Data-Driven Fault Diagnosis Method Based on Compressed Sensing and Improved Multiscale Network","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2943389092","doi":"https://doi.org/10.1109/tie.2019.2912763","mag":"2943389092"},"language":"en","primary_location":{"id":"doi:10.1109/tie.2019.2912763","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2019.2912763","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"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 Industrial Electronics","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/A5038147203","display_name":"Zhongxu Hu","orcid":"https://orcid.org/0000-0001-8236-7903"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhong-Xu Hu","raw_affiliation_strings":["School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100322552","display_name":"Yan Wang","orcid":"https://orcid.org/0000-0001-9324-4191"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Wang","raw_affiliation_strings":["Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, USA"],"affiliations":[{"raw_affiliation_string":"Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015351531","display_name":"Ming\u2010Feng Ge","orcid":"https://orcid.org/0000-0002-6828-0147"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming-Feng Ge","raw_affiliation_strings":["School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100454052","display_name":"Jie Liu","orcid":"https://orcid.org/0000-0002-0750-1030"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Liu","raw_affiliation_strings":["School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5038147203"],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":19.1599,"has_fulltext":false,"cited_by_count":213,"citation_normalized_percentile":{"value":0.99610356,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"67","issue":"4","first_page":"3216","last_page":"3225"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9962000250816345,"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":0.9962000250816345,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/softmax-function","display_name":"Softmax function","score":0.7772595882415771},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6830180287361145},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6485950350761414},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6085672378540039},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.6079561710357666},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5614620447158813},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5252673029899597},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4886487126350403},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.4839330315589905},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.4491182267665863},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4386642575263977},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4352014362812042},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4239538013935089},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3826150894165039}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.7772595882415771},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6830180287361145},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6485950350761414},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6085672378540039},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.6079561710357666},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5614620447158813},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5252673029899597},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4886487126350403},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.4839330315589905},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.4491182267665863},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4386642575263977},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4352014362812042},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4239538013935089},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3826150894165039},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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":1,"locations":[{"id":"doi:10.1109/tie.2019.2912763","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2019.2912763","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"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 Industrial Electronics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1086556306","display_name":null,"funder_award_id":"201606160048","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"},{"id":"https://openalex.org/G1595081637","display_name":null,"funder_award_id":"61703374","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/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1563088657","https://openalex.org/W2004039783","https://openalex.org/W2049550263","https://openalex.org/W2053741029","https://openalex.org/W2097117768","https://openalex.org/W2145096794","https://openalex.org/W2183341477","https://openalex.org/W2184192902","https://openalex.org/W2219903032","https://openalex.org/W2258884143","https://openalex.org/W2287029277","https://openalex.org/W2296616510","https://openalex.org/W2464878551","https://openalex.org/W2501044044","https://openalex.org/W2517756674","https://openalex.org/W2518980640","https://openalex.org/W2606521772","https://openalex.org/W2692693673","https://openalex.org/W2725323272","https://openalex.org/W2734669076","https://openalex.org/W2744604411","https://openalex.org/W2763269460","https://openalex.org/W2765284480","https://openalex.org/W2767234670","https://openalex.org/W2773064291","https://openalex.org/W2792461833","https://openalex.org/W2794869810","https://openalex.org/W2803884688","https://openalex.org/W2810484858","https://openalex.org/W2898375427","https://openalex.org/W2964350391","https://openalex.org/W4250955649"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W3108503355","https://openalex.org/W3090555870","https://openalex.org/W4226420367","https://openalex.org/W2962876041","https://openalex.org/W3022820045","https://openalex.org/W2801655600","https://openalex.org/W4323060069","https://openalex.org/W2997424368"],"abstract_inverted_index":{"The":[0,21,146,177],"diagnosis":[1,26,89,171,201],"of":[2,6,18,23,38,66,119,173,179,196],"the":[3,13,24,36,59,107,117,124,130,143,170,174,180,197],"key":[4,181],"components":[5,182],"rotating":[7,110],"machinery":[8],"systems":[9],"is":[10,50,70,101,113,127,150,160,191],"essential":[11],"for":[12,77,142,155,162],"production":[14],"efficiency":[15],"and":[16,73,96,105,164],"quality":[17],"manufacturing":[19],"processes.":[20],"performance":[22,172],"traditional":[25],"method":[27,49,61,90],"depends":[28],"heavily":[29],"on":[30,35,92],"feature":[31,54],"extraction,":[32],"which":[33,69,123],"relies":[34],"degree":[37],"individual's":[39],"expertise":[40],"or":[41],"prior":[42],"knowledge.":[43],"Recently,":[44],"a":[45,63,75,85,186],"deep":[46,166],"learning":[47,163],"(DL)":[48],"applied":[51],"to":[52,103,115,137,152,193],"automate":[53],"extraction.":[55],"However,":[56],"training":[57,140],"in":[58,80,109],"DL":[60,175],"requires":[62],"massive":[64],"amount":[65,118],"sensor":[67],"data,":[68,121],"time":[71],"consuming":[72],"poses":[74],"challenge":[76],"its":[78],"applications":[79],"engineering.":[81],"In":[82],"this":[83],"paper,":[84],"new":[86],"data-driven":[87,199],"fault":[88,125,200],"based":[91],"compressed":[93,148],"sensing":[94],"(CS)":[95],"improved":[97],"multiscale":[98],"network":[99],"(IMSN)":[100],"proposed":[102,198],"recognize":[104],"classify":[106],"faults":[108,178],"machinery.":[111],"CS":[112],"used":[114,136],"reduce":[116],"raw":[120],"from":[122,185],"information":[126],"discovered.":[128],"At":[129],"same":[131],"time,":[132],"it":[133],"can":[134],"be":[135],"generate":[138],"sufficient":[139],"samples":[141],"subsequent":[144],"learning.":[145,157],"one-dimensional":[147],"signal":[149],"converted":[151],"two-dimensional":[153],"image":[154],"further":[156],"An":[158],"IMSN":[159],"established":[161],"obtaining":[165],"features.":[167],"It":[168],"improves":[169],"process.":[176],"are":[183],"identified":[184],"softmax":[187],"model.":[188],"Experimental":[189],"analysis":[190],"performed":[192],"verify":[194],"effectiveness":[195],"method.":[202]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":38},{"year":2023,"cited_by_count":31},{"year":2022,"cited_by_count":44},{"year":2021,"cited_by_count":37},{"year":2020,"cited_by_count":23},{"year":2019,"cited_by_count":10}],"updated_date":"2026-03-22T08:09:32.410652","created_date":"2025-10-10T00:00:00"}
