{"id":"https://openalex.org/W7225620380","doi":"https://doi.org/10.1038/s41598-026-79327-y","title":"Physics-informed domain adaptation for synthetic-to-real bearing fault diagnosis with healthy-only target data","display_name":"Physics-informed domain adaptation for synthetic-to-real bearing fault diagnosis with healthy-only target data","publication_year":2026,"publication_date":"2026-11-09","ids":{"openalex":"https://openalex.org/W7225620380","doi":"https://doi.org/10.1038/s41598-026-79327-y"},"language":"en","primary_location":{"id":"doi:10.1038/s41598-026-79327-y","doi":"https://doi.org/10.1038/s41598-026-79327-y","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-79327-y","pdf_url":"https://www.nature.com/articles/s41598-026-79327-y_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.nature.com/articles/s41598-026-79327-y_reference.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139698714","display_name":"Iaroslav Biziarkin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I172901346","display_name":"St Petersburg University","ror":"https://ror.org/023znxa73","country_code":"RU","type":"education","lineage":["https://openalex.org/I172901346"]}],"countries":["RU"],"is_corresponding":true,"raw_author_name":"Iaroslav Biziarkin","raw_affiliation_strings":["Saint Petersburg University, Universitetskaya Embankment, 7/9, Saint Petersburg, 199034, Russian Federation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saint Petersburg University, Universitetskaya Embankment, 7/9, Saint Petersburg, 199034, Russian Federation","institution_ids":["https://openalex.org/I172901346"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139713023","display_name":"Nikolai Litvinov","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I172901346","display_name":"St Petersburg University","ror":"https://ror.org/023znxa73","country_code":"RU","type":"education","lineage":["https://openalex.org/I172901346"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Nikolai Litvinov","raw_affiliation_strings":["Saint Petersburg University, Universitetskaya Embankment, 7/9, Saint Petersburg, 199034, Russian Federation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saint Petersburg University, Universitetskaya Embankment, 7/9, Saint Petersburg, 199034, Russian Federation","institution_ids":["https://openalex.org/I172901346"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002492418","display_name":"Vladimir Vladislavovich Korkhov","orcid":"https://orcid.org/0000-0003-2458-3194","observed_orcids":["https://orcid.org/0000-0003-2458-3194"]},"institutions":[{"id":"https://openalex.org/I172901346","display_name":"St Petersburg University","ror":"https://ror.org/023znxa73","country_code":"RU","type":"education","lineage":["https://openalex.org/I172901346"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Vladimir Korkhov","raw_affiliation_strings":["Saint Petersburg University, Universitetskaya Embankment, 7/9, Saint Petersburg, 199034, Russian Federation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saint Petersburg University, Universitetskaya Embankment, 7/9, Saint Petersburg, 199034, Russian Federation","institution_ids":["https://openalex.org/I172901346"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5139698714"],"corresponding_institution_ids":["https://openalex.org/I172901346"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":{"value":2690,"currency":"USD","value_usd":2690},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":1.0,"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":1.0,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.0,"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":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bearing-fault-diagnosis","display_name":"bearing fault diagnosis","score":0.9959999918937683},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"domain adaptation","score":0.7950000166893005},{"id":"https://openalex.org/keywords/physics-informed-neural-networks","display_name":"physics-informed neural networks","score":0.7020000219345093},{"id":"https://openalex.org/keywords/synthetic-to-real-transfer","display_name":"synthetic-to-real transfer","score":0.875},{"id":"https://openalex.org/keywords/envelope-spectrum","display_name":"envelope spectrum","score":0.6629999876022339},{"id":"https://openalex.org/keywords/domain-alignment","display_name":"domain alignment","score":0.8140000104904175},{"id":"https://openalex.org/keywords/paderborn","display_name":"Paderborn","score":0.8700000047683716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7669000029563904},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.7232000231742859},{"id":"https://openalex.org/C199978012","wikidata":"https://www.wikidata.org/wiki/Q1273815","display_name":"Bearing (navigation)","level":2,"score":0.6201000213623047},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6165000200271606},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5600000023841858},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5436999797821045},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.48069998621940613},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.47760000824928284},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4681999981403351},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4449000060558319},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43470001220703125},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.40709999203681946},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3865000009536743},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.3666999936103821},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.34880000352859497},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3375000059604645},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3319999873638153},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.3312999904155731},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3075999915599823},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1038/s41598-026-79327-y","doi":"https://doi.org/10.1038/s41598-026-79327-y","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-79327-y","pdf_url":"https://www.nature.com/articles/s41598-026-79327-y_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1038/s41598-026-79327-y","doi":"https://doi.org/10.1038/s41598-026-79327-y","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-79327-y","pdf_url":"https://www.nature.com/articles/s41598-026-79327-y_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225620380.pdf","grobid_xml":"https://content.openalex.org/works/W7225620380.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W243674440","https://openalex.org/W1836465849","https://openalex.org/W1964511482","https://openalex.org/W2055776502","https://openalex.org/W2530133016","https://openalex.org/W2732499510","https://openalex.org/W2765407302","https://openalex.org/W2793888044","https://openalex.org/W2795155917","https://openalex.org/W2904460913","https://openalex.org/W2908510526","https://openalex.org/W2937019265","https://openalex.org/W2997151494","https://openalex.org/W3007769536","https://openalex.org/W3018378048","https://openalex.org/W3097678888","https://openalex.org/W3179976630","https://openalex.org/W4283080286","https://openalex.org/W4403210787","https://openalex.org/W4403562978","https://openalex.org/W4404028618","https://openalex.org/W4408039889","https://openalex.org/W4416830716","https://openalex.org/W4417256406","https://openalex.org/W7129598829","https://openalex.org/W7161702812"],"related_works":["https://openalex.org/W4414057067","https://openalex.org/W4399794761","https://openalex.org/W7221010065","https://openalex.org/W7125966460","https://openalex.org/W7083589170","https://openalex.org/W7196948726","https://openalex.org/W7223653466","https://openalex.org/W4317254631","https://openalex.org/W4220654061","https://openalex.org/W4401836816"],"abstract_inverted_index":{"Reliable":[0],"bearing":[1,109],"fault":[2,8],"diagnosis":[3],"is":[4,44,139],"difficult":[5,155],"when":[6],"real":[7],"data":[9,165],"cannot":[10],"be":[11],"collected":[12],"without":[13,99],"risking":[14],"machine":[15],"damage.":[16],"We":[17,52],"study":[18],"a":[19,58,69,75,80,104,142,167],"synthetic-to-real":[20],"setting":[21],"in":[22],"which":[23],"training":[24],"uses":[25],"labelled":[26],"synthetic":[27],"faults":[28],"and":[29,73,90,117,123,125,150],"recordings":[30],"known":[31],"to":[32],"represent":[33],"healthy":[34,65],"operation":[35],"of":[36],"the":[37,95,147],"target":[38,97,101,164],"machine,":[39],"while":[40,171],"no":[41],"target-fault":[42],"sample":[43],"available":[45,96],"for":[46,156],"training,":[47],"adaptation,":[48],"or":[49],"model":[50],"selection.":[51],"propose":[53],"Healthy-Referenced":[54],"Physics-informed":[55],"Diagnosis":[56],"(HRPD),":[57],"framework":[59],"that":[60,173],"subtracts":[61],"each":[62],"domain\u2019s":[63],"mean":[64],"envelope-order":[66],"spectrum,":[67],"retains":[68],"complementary":[70],"log-magnitude":[71],"channel,":[72],"combines":[74],"temporal":[76],"convolutional":[77],"encoder":[78],"with":[79],"physics":[81],"branch":[82],"built":[83],"from":[84,146],"characteristic-order":[85],"harmonics.":[86],"A":[87],"cosine-prototype":[88],"classifier":[89],"healthy-class-restricted":[91],"domain":[92],"alignment":[93],"use":[94],"information":[98],"observing":[100],"faults.":[102],"Under":[103],"common-data":[105],"protocol":[106],"on":[107,114,127],"four":[108],"benchmarks,":[110],"HRPD":[111],"ranks":[112],"first":[113],"CWRU,":[115],"MFPT,":[116],"Paderborn":[118,151],"(balanced":[119],"accuracy":[120],"0.643,":[121],"0.979,":[122],"0.545)":[124],"second":[126],"XJTU-SY":[128,136],"(0.638).":[129],"The":[130],"results":[131],"also":[132],"expose":[133],"clear":[134],"limitations:":[135],"inner-race":[137],"damage":[138],"dominated":[140],"by":[141,177],"shaft-synchronous":[143],"component":[144],"absent":[145],"geometry-based":[148],"source,":[149],"operational":[152],"wear":[153],"remains":[154,175],"every":[157],"evaluated":[158],"framework.":[159],"These":[160],"findings":[161],"support":[162],"healthy-only":[163],"as":[166],"practical":[168],"calibration":[169],"resource":[170],"showing":[172],"transfer":[174],"constrained":[176],"synthetic-source":[178],"fidelity.":[179]},"counts_by_year":[],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2026-11-10T00:00:00"}
