{"id":"https://openalex.org/W3084079971","doi":"https://doi.org/10.1109/icphm49022.2020.9187058","title":"A Novel Evaluation Framework for Unsupervised Domain Adaption on Remaining Useful Lifetime Estimation","display_name":"A Novel Evaluation Framework for Unsupervised Domain Adaption on Remaining Useful Lifetime Estimation","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3084079971","doi":"https://doi.org/10.1109/icphm49022.2020.9187058","mag":"3084079971"},"language":"en","primary_location":{"id":"doi:10.1109/icphm49022.2020.9187058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icphm49022.2020.9187058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Prognostics and Health Management (ICPHM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5078324628","display_name":"Tilman Krokotsch","orcid":"https://orcid.org/0000-0002-5512-9712"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tilman Krokotsch","raw_affiliation_strings":["Electronic Measurement and Diagnostic Technology, Technische Universit\u00e4t, Berlin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronic Measurement and Diagnostic Technology, Technische Universit\u00e4t, Berlin","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023787362","display_name":"Mirko Knaak","orcid":null},"institutions":[{"id":"https://openalex.org/I137230718","display_name":"Ingenieurgesellschaft Auto und Verkehr (Germany)","ror":"https://ror.org/00j4h9q86","country_code":"DE","type":"company","lineage":["https://openalex.org/I137230718"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mirko Knaak","raw_affiliation_strings":["Thermodynamics & Power Systems, IAV GmbH"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Thermodynamics & Power Systems, IAV GmbH","institution_ids":["https://openalex.org/I137230718"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043061050","display_name":"Clemens G\u00fchmann","orcid":"https://orcid.org/0000-0002-2865-0078"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Clemens Guhmann","raw_affiliation_strings":["Electronic Measurement and Diagnostic Technology, Technische Universit\u00e4t, Berlin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronic Measurement and Diagnostic Technology, Technische Universit\u00e4t, Berlin","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.23,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.49218042,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9962999820709229,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9962999820709229,"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"}},{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9218999743461609,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9009000062942505,"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":0.7806169390678406},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.6608214378356934},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.58412104845047},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5434965491294861},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5226980447769165},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5009293556213379},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.446696937084198},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10937368869781494},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07190564274787903}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7806169390678406},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.6608214378356934},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.58412104845047},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5434965491294861},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5226980447769165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5009293556213379},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.446696937084198},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10937368869781494},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07190564274787903},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icphm49022.2020.9187058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icphm49022.2020.9187058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Prognostics and Health Management (ICPHM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"id":"https://metadata.un.org/sdg/12","display_name":"Responsible consumption and production"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W809430598","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1565327149","https://openalex.org/W1686810756","https://openalex.org/W1731081199","https://openalex.org/W1882958252","https://openalex.org/W1982275278","https://openalex.org/W2004273576","https://openalex.org/W2081283602","https://openalex.org/W2099635155","https://openalex.org/W2110787940","https://openalex.org/W2114106396","https://openalex.org/W2115403315","https://openalex.org/W2149933564","https://openalex.org/W2159291411","https://openalex.org/W2279034837","https://openalex.org/W2395579298","https://openalex.org/W2415594836","https://openalex.org/W2478454054","https://openalex.org/W2515979703","https://openalex.org/W2617137613","https://openalex.org/W2744067593","https://openalex.org/W2751528152","https://openalex.org/W2772084711","https://openalex.org/W2792764867","https://openalex.org/W2795155917","https://openalex.org/W2896457183","https://openalex.org/W2902443160","https://openalex.org/W2904218127","https://openalex.org/W2921921216","https://openalex.org/W2958771129","https://openalex.org/W2962835968","https://openalex.org/W2963341956","https://openalex.org/W2963826681","https://openalex.org/W2964278684","https://openalex.org/W2975761873","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6633949838","https://openalex.org/W6637373629","https://openalex.org/W6637618735","https://openalex.org/W6639480849","https://openalex.org/W6671258673","https://openalex.org/W6683633756","https://openalex.org/W6695692224","https://openalex.org/W6713955831","https://openalex.org/W6743095615","https://openalex.org/W6749825310","https://openalex.org/W6750109254","https://openalex.org/W6755207826","https://openalex.org/W6760315093"],"related_works":["https://openalex.org/W2576994247","https://openalex.org/W3196155444","https://openalex.org/W4321844043","https://openalex.org/W3210156800","https://openalex.org/W4390062853","https://openalex.org/W4297883248","https://openalex.org/W4255830763","https://openalex.org/W1583266947","https://openalex.org/W4286799911","https://openalex.org/W3165437720"],"abstract_inverted_index":{"Unsupervised":[0],"Domain":[1],"Adaption":[2],"(DA)":[3],"is":[4,41,75],"an":[5,122],"approach":[6],"for":[7,31,39,47,65,99],"adapting":[8],"a":[9,52,56,95],"data-driven":[10],"model":[11],"to":[12],"new":[13],"data":[14],"without":[15],"labels.":[16],"Recent":[17],"work":[18],"on":[19,91,134],"Remaining":[20],"Useful":[21],"Lifetime":[22],"(RUL)":[23],"estimation":[24],"of":[25,42,59,89,110,116,126],"aero":[26],"engines":[27],"yielded":[28],"promising":[29],"results":[30],"this":[32],"approach.":[33],"However,":[34],"the":[35,78,108,131],"current":[36,79],"evaluation":[37,97],"framework":[38,80,98],"DA":[40,70,90,127,136,142],"limited":[43],"significance":[44],"when":[45],"used":[46],"RUL":[48,104,145],"estimation.":[49],"It":[50,74,120],"assumes":[51],"use":[53],"case":[54],"where":[55],"large":[57],"number":[58,109],"fully":[60],"degraded":[61],"systems":[62,112],"are":[63],"available":[64,111],"adaption,":[66],"which":[67],"makes":[68],"unsupervised":[69,100,141],"in":[71,103],"itself":[72],"unnecessary.":[73],"shown":[76],"that":[77,106,140],"overestimates":[81],"adaption":[82],"performance":[83,124],"and":[84,113,138],"obscures":[85],"potential,":[86],"negative":[87],"effects":[88],"performance.":[92],"We":[93,129],"propose":[94],"novel":[96],"DA,":[101],"specialized":[102],"estimation,":[105],"takes":[107],"their":[114],"grade":[115],"degradation":[117],"into":[118],"account.":[119],"enables":[121],"informed":[123],"comparison":[125],"methods.":[128],"detail":[130],"framework's":[132],"capabilities":[133],"two":[135],"methods":[137],"show":[139],"delivers":[143],"improved":[144],"estimations":[146],"under":[147],"real-life":[148],"scenarios,":[149],"as":[150],"well.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
