{"id":"https://openalex.org/W2904570575","doi":"https://doi.org/10.1109/access.2018.2885816","title":"Multi-Fault Rapid Diagnosis for Wind Turbine Gearbox Using Sparse Bayesian Extreme Learning Machine","display_name":"Multi-Fault Rapid Diagnosis for Wind Turbine Gearbox Using Sparse Bayesian Extreme Learning Machine","publication_year":2018,"publication_date":"2018-12-12","ids":{"openalex":"https://openalex.org/W2904570575","doi":"https://doi.org/10.1109/access.2018.2885816","mag":"2904570575"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2885816","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2885816","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08573761.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08573761.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055125557","display_name":"Jianhua Zhong","orcid":"https://orcid.org/0000-0002-6224-003X"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian-Hua Zhong","raw_affiliation_strings":["School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-6224-003X","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020220195","display_name":"Jun Zhang","orcid":"https://orcid.org/0000-0003-3232-5195"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zhang","raw_affiliation_strings":["School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008568125","display_name":"Jiejunyi Liang","orcid":"https://orcid.org/0000-0001-8549-0261"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jiejunyi Liang","raw_affiliation_strings":["School of Mechanical and Mechatronics Engineering, University of Technology Sydney, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0001-8549-0261","affiliations":[{"raw_affiliation_string":"School of Mechanical and Mechatronics Engineering, University of Technology Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100727455","display_name":"Haiqing Wang","orcid":"https://orcid.org/0000-0001-5491-2628"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiqing Wang","raw_affiliation_strings":["School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5491-2628","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.8348,"has_fulltext":true,"cited_by_count":44,"citation_normalized_percentile":{"value":0.94161546,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"7","issue":null,"first_page":"773","last_page":"781"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T10663","display_name":"Advanced Battery Technologies Research","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T12676","display_name":"Machine Learning and ELM","score":0.989300012588501,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7073134779930115},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.7054629325866699},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5866488814353943},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5702661275863647},{"id":"https://openalex.org/keywords/wind-power","display_name":"Wind power","score":0.5633354783058167},{"id":"https://openalex.org/keywords/relevance-vector-machine","display_name":"Relevance vector machine","score":0.5613024234771729},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5342727303504944},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44369906187057495},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4408543109893799},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.42017993330955505},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35500454902648926},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24021610617637634}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7073134779930115},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.7054629325866699},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5866488814353943},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5702661275863647},{"id":"https://openalex.org/C78600449","wikidata":"https://www.wikidata.org/wiki/Q43302","display_name":"Wind power","level":2,"score":0.5633354783058167},{"id":"https://openalex.org/C14948415","wikidata":"https://www.wikidata.org/wiki/Q7310972","display_name":"Relevance vector machine","level":3,"score":0.5613024234771729},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5342727303504944},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44369906187057495},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4408543109893799},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.42017993330955505},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35500454902648926},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24021610617637634},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2018.2885816","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2885816","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08573761.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e19e329b39d440bbb78beb57303027b5","is_oa":true,"landing_page_url":"https://doaj.org/article/e19e329b39d440bbb78beb57303027b5","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":"IEEE Access, Vol 7, Pp 773-781 (2019)","raw_type":"article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/140277","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/140277","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2885816","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2885816","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08573761.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G135024254","display_name":null,"funder_award_id":"51375013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3556515513","display_name":"\u5c11\u9f7f\u5dee\u9525\u9f7f\u8f6e\u7ae0\u52a8\u51cf\u901f\u5668\u591a\u6e90\u8bef\u5dee\u6270\u52a8\u673a\u5236\u4e0e\u7cbe\u5ea6\u9000\u5316\u673a\u7406\u7814\u7a76","funder_award_id":"51875105","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"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2904570575.pdf","grobid_xml":"https://content.openalex.org/works/W2904570575.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W83480120","https://openalex.org/W1967559043","https://openalex.org/W1976676614","https://openalex.org/W1980303241","https://openalex.org/W1986397312","https://openalex.org/W1990067914","https://openalex.org/W2002034577","https://openalex.org/W2002305563","https://openalex.org/W2009248907","https://openalex.org/W2014632329","https://openalex.org/W2019581905","https://openalex.org/W2021497603","https://openalex.org/W2023719938","https://openalex.org/W2026131661","https://openalex.org/W2028723458","https://openalex.org/W2029783486","https://openalex.org/W2031423206","https://openalex.org/W2034741007","https://openalex.org/W2035094917","https://openalex.org/W2036259765","https://openalex.org/W2040647667","https://openalex.org/W2041432213","https://openalex.org/W2057361254","https://openalex.org/W2066169218","https://openalex.org/W2066980082","https://openalex.org/W2075165644","https://openalex.org/W2078994304","https://openalex.org/W2082274261","https://openalex.org/W2094099988","https://openalex.org/W2120390927","https://openalex.org/W2121598944","https://openalex.org/W2160987092","https://openalex.org/W2170864940","https://openalex.org/W2172070753","https://openalex.org/W2318040200","https://openalex.org/W2388433262","https://openalex.org/W2462832583","https://openalex.org/W2488902184","https://openalex.org/W2557231223","https://openalex.org/W2580703932","https://openalex.org/W2586037054","https://openalex.org/W2613103149","https://openalex.org/W2766245932","https://openalex.org/W2767837287","https://openalex.org/W2770280398","https://openalex.org/W2773470152","https://openalex.org/W2803881197","https://openalex.org/W2873996253","https://openalex.org/W4233480136","https://openalex.org/W4235457221","https://openalex.org/W4285719527","https://openalex.org/W6659332748","https://openalex.org/W6699671966","https://openalex.org/W6719134154","https://openalex.org/W6753253582"],"related_works":["https://openalex.org/W2010005619","https://openalex.org/W2066952721","https://openalex.org/W2565312173","https://openalex.org/W2683383161","https://openalex.org/W2335152656","https://openalex.org/W3147035969","https://openalex.org/W2359936972","https://openalex.org/W2383027800","https://openalex.org/W2206547991","https://openalex.org/W2104936869"],"abstract_inverted_index":{"In":[0,43,156],"order":[1],"to":[2,69,163],"reduce":[3],"operation":[4],"and":[5,9,39,60,93,109,124,131,135,150,208],"maintenance":[6],"costs,":[7],"reliability,":[8],"quick":[10],"response":[11],"capability":[12],"of":[13,45,97,113,174],"multi-fault":[14,167,201],"intelligent":[15],"diagnosis":[16],"for":[17],"the":[18,54,71,84,94,98,103,107,110,129,172,175,196],"wind":[19,187,203],"turbine":[20,188,204],"system":[21],"are":[22,50,121],"becoming":[23],"more":[24,73,122,133,209],"important.":[25],"This":[26],"paper":[27],"proposes":[28],"a":[29,165,185],"rapid":[30],"data-driven":[31],"fault":[32,48,177],"diagnostic":[33,168,178],"method,":[34],"which":[35],"integrates":[36],"data":[37,46],"pre-processing":[38],"machine":[40,119,154],"learning":[41,111,118],"techniques.":[42,62,214],"terms":[44],"pre-processing,":[47],"features":[49],"extracted":[51],"by":[52,82],"using":[53],"proposed":[55,176,197],"modified":[56],"Hilbert\u2013Huang":[57],"transforms":[58],"(HHT)":[59],"correlation":[61],"Then,":[63],"time":[64,89],"domain":[65,90],"analysis":[66],"is":[67,161,181],"conducted":[68],"make":[70],"feature":[72],"concise.":[74],"A":[75],"dimension":[76],"vector":[77,153],"will":[78],"then":[79],"be":[80],"constructed":[81],"including":[83],"intrinsic":[85],"mode":[86],"function":[87],"energy,":[88],"statistical":[91],"features,":[92],"maximum":[95],"value":[96],"HHT":[99],"marginal":[100],"spectrum.":[101],"On":[102],"other":[104],"hand,":[105],"as":[106,144],"architecture":[108],"algorithm":[112],"pairwise-coupled":[114,145,151],"sparse":[115],"Bayesian":[116],"extreme":[117],"(PC-SBELM)":[120],"concise":[123],"effective,":[125],"it":[126,180],"could":[127],"identify":[128],"single-":[130],"simultaneous-fault":[132],"quickly":[134],"precisely":[136],"when":[137],"compared":[138],"with":[139],"traditional":[140,212],"identification":[141,213],"techniques":[142],"such":[143],"probabilistic":[146],"neural":[147],"networks":[148],"(PC-PNN)":[149],"relevance":[152],"(PC-RVM).":[155],"this":[157],"case":[158],"study,":[159],"PC-SBELM":[160],"applied":[162],"build":[164],"real-time":[166],"system.":[169,190],"To":[170],"verify":[171],"effectiveness":[173],"framework,":[179],"carried":[182],"out":[183],"on":[184],"real":[186],"gearbox":[189,205],"The":[191],"evaluation":[192],"results":[193],"show":[194],"that":[195],"framework":[198],"can":[199],"detect":[200],"in":[202],"much":[206],"faster":[207],"accurately":[210],"than":[211]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":5}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}