{"id":"https://openalex.org/W2980887226","doi":"https://doi.org/10.1109/access.2019.2948291","title":"A Novel RLS-KS Method for Parameter Estimation in Particle Filtering-Based Fatigue Crack Growth Prognostics","display_name":"A Novel RLS-KS Method for Parameter Estimation in Particle Filtering-Based Fatigue Crack Growth Prognostics","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2980887226","doi":"https://doi.org/10.1109/access.2019.2948291","mag":"2980887226"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2948291","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2948291","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08876693.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/ielx7/6287639/8600701/08876693.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100633299","display_name":"Xiaopeng Liu","orcid":"https://orcid.org/0000-0001-5820-0812"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaopeng Liu","raw_affiliation_strings":["School of Reliability and Systems Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5820-0812","affiliations":[{"raw_affiliation_string":"School of Reliability and Systems Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101798257","display_name":"Weifang Zhang","orcid":"https://orcid.org/0000-0002-6222-278X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weifang Zhang","raw_affiliation_strings":["School of Reliability and Systems Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Reliability and Systems Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101593082","display_name":"Xuerong Liu","orcid":"https://orcid.org/0000-0002-2897-7871"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuerong Liu","raw_affiliation_strings":["School of Reliability and Systems Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Reliability and Systems Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081209439","display_name":"Wei Dai","orcid":"https://orcid.org/0000-0002-7376-6977"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Dai","raw_affiliation_strings":["School of Reliability and Systems Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7376-6977","affiliations":[{"raw_affiliation_string":"School of Reliability and Systems Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070547032","display_name":"Guicui Fu","orcid":"https://orcid.org/0000-0001-6295-3454"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guicui Fu","raw_affiliation_strings":["School of Reliability and Systems Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Reliability and Systems Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.8047,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.7424709,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"7","issue":null,"first_page":"156764","last_page":"156778"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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":0.995199978351593,"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/prognostics","display_name":"Prognostics","score":0.9930398464202881},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6965309381484985},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.5689517259597778},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47034862637519836},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.45975351333618164},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4326735734939575},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.3357699513435364},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.30238065123558044},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.2876153886318207},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2271115779876709},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20784834027290344},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19995909929275513},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.18680229783058167}],"concepts":[{"id":"https://openalex.org/C129364497","wikidata":"https://www.wikidata.org/wiki/Q3042561","display_name":"Prognostics","level":2,"score":0.9930398464202881},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6965309381484985},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.5689517259597778},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47034862637519836},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.45975351333618164},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4326735734939575},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3357699513435364},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.30238065123558044},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.2876153886318207},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2271115779876709},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20784834027290344},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19995909929275513},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.18680229783058167},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2948291","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2948291","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08876693.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:344d9c75f9754c93acf3c0e2a9b266b4","is_oa":true,"landing_page_url":"https://doaj.org/article/344d9c75f9754c93acf3c0e2a9b266b4","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 156764-156778 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2948291","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2948291","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08876693.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.44999998807907104,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G2415310445","display_name":null,"funder_award_id":"JSZL2017601C002","funder_id":"https://openalex.org/F4320323970","funder_display_name":"Ministry of Industry and Information Technology of the People's Republic of China"},{"id":"https://openalex.org/G2954607207","display_name":null,"funder_award_id":"JSZL JSZL2017601C002","funder_id":"https://openalex.org/F4320323970","funder_display_name":"Ministry of Industry and Information Technology of the People's Republic of China"}],"funders":[{"id":"https://openalex.org/F4320323970","display_name":"Ministry of Industry and Information Technology of the People's Republic of China","ror":"https://ror.org/0385nmy68"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2980887226.pdf","grobid_xml":"https://content.openalex.org/works/W2980887226.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W596967750","https://openalex.org/W819928789","https://openalex.org/W1481913965","https://openalex.org/W1483307070","https://openalex.org/W1630643874","https://openalex.org/W1814615119","https://openalex.org/W2000999339","https://openalex.org/W2008409680","https://openalex.org/W2017594537","https://openalex.org/W2022228946","https://openalex.org/W2027595608","https://openalex.org/W2033336377","https://openalex.org/W2042311265","https://openalex.org/W2047949424","https://openalex.org/W2051319254","https://openalex.org/W2052706427","https://openalex.org/W2062758573","https://openalex.org/W2087980440","https://openalex.org/W2098091224","https://openalex.org/W2126736494","https://openalex.org/W2134788745","https://openalex.org/W2148613679","https://openalex.org/W2150606224","https://openalex.org/W2187422466","https://openalex.org/W2291116836","https://openalex.org/W2491335332","https://openalex.org/W2509364735","https://openalex.org/W2538208118","https://openalex.org/W2588697246","https://openalex.org/W2606195371","https://openalex.org/W2617588148","https://openalex.org/W2734884913","https://openalex.org/W2737676087","https://openalex.org/W2760955178","https://openalex.org/W2761163042","https://openalex.org/W2767251665","https://openalex.org/W2770203925","https://openalex.org/W2773619359","https://openalex.org/W2774992281","https://openalex.org/W2791632718","https://openalex.org/W2800516611","https://openalex.org/W2890585303","https://openalex.org/W2897033773","https://openalex.org/W2900724283","https://openalex.org/W2908953301","https://openalex.org/W2941697499","https://openalex.org/W2947106155","https://openalex.org/W3103934441","https://openalex.org/W3186015212","https://openalex.org/W4298330376","https://openalex.org/W6799136968"],"related_works":["https://openalex.org/W2310476526","https://openalex.org/W3213192587","https://openalex.org/W2144291498","https://openalex.org/W2535730979","https://openalex.org/W3193475673","https://openalex.org/W2370073012","https://openalex.org/W4386567722","https://openalex.org/W2168646784","https://openalex.org/W2965730886","https://openalex.org/W2030958945"],"abstract_inverted_index":{"The":[0,59,142,165],"accurate":[1],"prognosis":[2,112],"of":[3,21,40,61,85],"fatigue":[4],"crack":[5,71],"growth":[6],"(FCG)":[7],"is":[8,51,82,133,145],"vital":[9],"for":[10,37,135,188],"securing":[11],"structural":[12,22],"safety":[13],"and":[14,151,160,179],"developing":[15],"maintenance":[16],"plans.":[17],"With":[18],"the":[19,27,43,47,62,70,74,89,95,101,155,170],"development":[20],"health":[23],"monitoring":[24],"(SHM)":[25],"technology,":[26],"particle":[28],"filter":[29],"(PF)":[30],"has":[31],"been":[32],"considered":[33],"a":[34,83,99,106,125],"promising":[35],"tool":[36],"online":[38],"prognostics":[39,178,190],"FCG.":[41],"Among":[42],"existing":[44],"FCG":[45,57,140,189],"models,":[46],"traditional":[48],"Paris-Erdogan":[49,63],"model":[50,64],"most":[52],"commonly":[53],"used":[54],"in":[55,73,122,138],"PF-based":[56,139],"prognostics.":[58,141],"parameters":[60,90,116],"can":[65,173],"be":[66],"estimated":[67],"together":[68],"with":[69,154,192],"state":[72],"PF":[75],"framework.":[76],"However,":[77],"we":[78],"find":[79],"that":[80,169],"there":[81],"problem":[84],"\u201cCoordinated":[86],"Change\u201d":[87],"when":[88],"priors":[91],"are":[92],"far":[93],"from":[94],"true":[96],"values.":[97],"As":[98],"result,":[100],"filtering":[102],"results":[103,167],"appear":[104],"as":[105],"correct":[107,176],"remaining":[108],"useful":[109],"life":[110],"(RUL)":[111],"but":[113],"an":[114,148],"incorrect":[115],"estimation.":[117,181],"To":[118],"solve":[119],"this":[120,123,183],"problem,":[121],"paper,":[124],"novel":[126],"recursive":[127],"least":[128],"squares-kernel":[129],"smoothing":[130,162],"(RLS-KS)":[131],"method":[132,144,172,184],"proposed":[134,143],"parameter":[136,180],"estimation":[137],"validated":[146],"through":[147],"experimental":[149],"application;":[150],"then":[152],"compared":[153,191],"classic":[156,193],"artificial":[157],"evolution":[158],"(AE)":[159],"kernel":[161],"(KS)":[163],"methods.":[164,194],"validation":[166],"show":[168],"RLS-KS":[171],"provide":[174],"both":[175],"RUL":[177],"Moreover,":[182],"provides":[185],"better":[186],"performance":[187]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}