{"id":"https://openalex.org/W4402129549","doi":"https://doi.org/10.3390/s24175700","title":"New Fault Diagnosis Method for Rolling Bearings Based on Improved Residual Shrinkage Network Combined with Transfer Learning","display_name":"New Fault Diagnosis Method for Rolling Bearings Based on Improved Residual Shrinkage Network Combined with Transfer Learning","publication_year":2024,"publication_date":"2024-09-01","ids":{"openalex":"https://openalex.org/W4402129549","doi":"https://doi.org/10.3390/s24175700","pmid":"https://pubmed.ncbi.nlm.nih.gov/39275611"},"language":"en","primary_location":{"id":"doi:10.3390/s24175700","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24175700","pdf_url":"https://www.mdpi.com/1424-8220/24/17/5700/pdf?version=1725199057","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/1424-8220/24/17/5700/pdf?version=1725199057","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002442713","display_name":"Tieyang Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tieyang Sun","raw_affiliation_strings":["School of Mechanical Engineering, Xinjiang University, Urumqi 830046, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xinjiang University, Urumqi 830046, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026628307","display_name":"Jianxiong Gao","orcid":"https://orcid.org/0000-0002-2975-0150"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianxiong Gao","raw_affiliation_strings":["School of Mechanical Engineering, Xinjiang University, Urumqi 830046, China"],"raw_orcid":"https://orcid.org/0000-0002-2975-0150","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xinjiang University, Urumqi 830046, China","institution_ids":["https://openalex.org/I96908189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5026628307"],"corresponding_institution_ids":["https://openalex.org/I96908189"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":3.0005,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.9155712,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"24","issue":"17","first_page":"5700","last_page":"5700"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9959999918937683,"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":0.9959999918937683,"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/T11062","display_name":"Gear and Bearing Dynamics Analysis","score":0.988099992275238,"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/T13891","display_name":"Engineering Diagnostics and Reliability","score":0.9427000284194946,"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/noise","display_name":"Noise (video)","score":0.6401702165603638},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6021653413772583},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5802747011184692},{"id":"https://openalex.org/keywords/bearing","display_name":"Bearing (navigation)","score":0.5709933042526245},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5587946772575378},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5213802456855774},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5209842324256897},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.4549429714679718},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.452023983001709},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.451055645942688},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.44466227293014526},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4396686553955078},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.43521058559417725},{"id":"https://openalex.org/keywords/vibration","display_name":"Vibration","score":0.4317138195037842},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.42183393239974976},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4082770049571991},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3041319251060486},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2149064838886261},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.1285860240459442}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6401702165603638},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6021653413772583},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5802747011184692},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.5709933042526245},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5587946772575378},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5213802456855774},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5209842324256897},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.4549429714679718},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.452023983001709},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.451055645942688},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.44466227293014526},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4396686553955078},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.43521058559417725},{"id":"https://openalex.org/C198394728","wikidata":"https://www.wikidata.org/wiki/Q3695508","display_name":"Vibration","level":2,"score":0.4317138195037842},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.42183393239974976},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4082770049571991},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3041319251060486},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2149064838886261},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.1285860240459442},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/s24175700","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24175700","pdf_url":"https://www.mdpi.com/1424-8220/24/17/5700/pdf?version=1725199057","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:39275611","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39275611","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:11397943","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11397943","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11397943/pdf/sensors-24-05700.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:doaj.org/article:69c443e2127b48a786613aa805e0d50a","is_oa":false,"landing_page_url":"https://doaj.org/article/69c443e2127b48a786613aa805e0d50a","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 24, Iss 17, p 5700 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s24175700","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24175700","pdf_url":"https://www.mdpi.com/1424-8220/24/17/5700/pdf?version=1725199057","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":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402129549.pdf"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1975447418","https://openalex.org/W2010619950","https://openalex.org/W2053741029","https://openalex.org/W2054587233","https://openalex.org/W2533924129","https://openalex.org/W2560619756","https://openalex.org/W2752782242","https://openalex.org/W2775516437","https://openalex.org/W2898375427","https://openalex.org/W2915423430","https://openalex.org/W2918157303","https://openalex.org/W2969736276","https://openalex.org/W2991521245","https://openalex.org/W2996984945","https://openalex.org/W3022604663","https://openalex.org/W3036403470","https://openalex.org/W3091969210","https://openalex.org/W3126310674","https://openalex.org/W3134752243","https://openalex.org/W3160737447","https://openalex.org/W3174641600","https://openalex.org/W4224435980","https://openalex.org/W4285245107","https://openalex.org/W4297491405","https://openalex.org/W4297498779","https://openalex.org/W4303982360","https://openalex.org/W4311759245","https://openalex.org/W4320035132","https://openalex.org/W4320730622","https://openalex.org/W4360820497","https://openalex.org/W4362734841","https://openalex.org/W4377030229","https://openalex.org/W4386025873","https://openalex.org/W4386322155","https://openalex.org/W6852135183"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4295815739","https://openalex.org/W2915512385"],"abstract_inverted_index":{"The":[0,50,86,115,180],"fault":[1,15,18,105],"diagnosis":[2,19,28,106],"of":[3,11,14,103,107],"rolling":[4,128],"bearings":[5,108,129],"is":[6,40,52,65,120,135,166],"faced":[7],"with":[8,42,71,157],"the":[9,27,33,47,55,62,77,84,91,101,104,124,149,163,185],"problem":[10],"a":[12,68,72],"lack":[13],"data.":[16],"Currently,":[17],"based":[20],"on":[21,54,177],"traditional":[22],"convolutional":[23],"neural":[24],"networks":[25],"decreases":[26],"rate.":[29],"In":[30,137,160],"this":[31,138,161],"paper,":[32,139,162],"developed":[34],"adaptive":[35,116],"residual":[36],"shrinkage":[37],"network":[38],"model":[39,51,64],"combined":[41],"transfer":[43],"learning":[44],"to":[45,67,82,122,148],"solve":[46],"above":[48],"problems.":[49],"trained":[53,63],"Case":[56],"Western":[57],"Reserve":[58],"dataset,":[59],"and":[60,76,112,142],"then":[61],"migrated":[66],"small-sample":[69,98,178],"dataset":[70,81],"scaled-down":[73],"sample":[74],"size":[75],"Jiangnan":[78],"University":[79],"bearing":[80],"conduct":[83],"experiments.":[85],"experimental":[87,181],"results":[88,182],"show":[89,183],"that":[90,184],"proposed":[92],"method":[93],"can":[94,152],"efficiently":[95],"learn":[96],"from":[97],"datasets,":[99],"improving":[100],"accuracy":[102],"under":[109],"variable":[110,113],"loads":[111],"speeds.":[114],"parameter-rectified":[117],"linear":[118],"unit":[119],"utilized":[121],"adapt":[123],"nonlinear":[125],"transformation.":[126],"When":[127],"are":[130,146],"in":[131,173],"operation,":[132],"noise":[133,165,172,188],"production":[134],"inevitable.":[136],"soft":[140],"thresholding":[141],"an":[143],"attention":[144],"mechanism":[145],"added":[147],"model,":[150],"which":[151],"effectively":[153],"process":[154],"vibration":[155],"signals":[156],"strong":[158],"noise.":[159],"real":[164],"simulated":[167],"by":[168],"adding":[169],"Gaussian":[170],"white":[171],"migration":[174],"task":[175],"experiments":[176],"datasets.":[179],"algorithm":[186],"has":[187],"resistance.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}