{"id":"https://openalex.org/W4285156299","doi":"https://doi.org/10.1109/tr.2022.3179602","title":"Mixed-Input Bayesian Optimization Method for Structural Damage Diagnosis","display_name":"Mixed-Input Bayesian Optimization Method for Structural Damage Diagnosis","publication_year":2022,"publication_date":"2022-06-14","ids":{"openalex":"https://openalex.org/W4285156299","doi":"https://doi.org/10.1109/tr.2022.3179602"},"language":"en","primary_location":{"id":"doi:10.1109/tr.2022.3179602","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tr.2022.3179602","pdf_url":null,"source":{"id":"https://openalex.org/S87725633","display_name":"IEEE Transactions on Reliability","issn_l":"0018-9529","issn":["0018-9529","1558-1721"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Reliability","raw_type":"journal-article"},"type":"article","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/A5012594784","display_name":"Congfang Huang","orcid":"https://orcid.org/0000-0003-0488-1573"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Congfang Huang","raw_affiliation_strings":["Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA"],"raw_orcid":"https://orcid.org/0000-0003-0488-1573","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039290222","display_name":"Jaesung Lee","orcid":"https://orcid.org/0000-0001-7533-1865"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jaesung Lee","raw_affiliation_strings":["Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA"],"raw_orcid":"https://orcid.org/0000-0001-7533-1865","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100620969","display_name":"Yang Zhang","orcid":"https://orcid.org/0000-0001-8054-1429"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Zhang","raw_affiliation_strings":["Department of Mechanical Engineering, University of Connecticut, Storrs, CT, USA"],"raw_orcid":"https://orcid.org/0000-0001-8054-1429","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000499123","display_name":"Shiyu Zhou","orcid":"https://orcid.org/0000-0002-5902-8812"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shiyu Zhou","raw_affiliation_strings":["Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA"],"raw_orcid":"https://orcid.org/0000-0002-5902-8812","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087819768","display_name":"Jiong Tang","orcid":"https://orcid.org/0000-0002-6825-9049"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiong Tang","raw_affiliation_strings":["Department of Mechanical Engineering, University of Connecticut, Storrs, CT, USA"],"raw_orcid":"https://orcid.org/0000-0002-6825-9049","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5012594784"],"corresponding_institution_ids":["https://openalex.org/I135310074"],"apc_list":null,"apc_paid":null,"fwci":0.7542,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.73966476,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"72","issue":"2","first_page":"678","last_page":"691"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9979000091552734,"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/T11220","display_name":"Water Systems and Optimization","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"}}],"keywords":[{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6261183619499207},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.6021504402160645},{"id":"https://openalex.org/keywords/surrogate-model","display_name":"Surrogate model","score":0.5723250508308411},{"id":"https://openalex.org/keywords/structural-health-monitoring","display_name":"Structural health monitoring","score":0.5681446194648743},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5488201379776001},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5348206162452698},{"id":"https://openalex.org/keywords/admittance","display_name":"Admittance","score":0.5082442164421082},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4977469742298126},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.48790356516838074},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.484224796295166},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.44681552052497864},{"id":"https://openalex.org/keywords/finite-element-method","display_name":"Finite element method","score":0.44614121317863464},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.43264010548591614},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4267447590827942},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37667596340179443},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.27204060554504395},{"id":"https://openalex.org/keywords/electrical-impedance","display_name":"Electrical impedance","score":0.2118161916732788},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21069681644439697},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17946496605873108},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17579826712608337},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.14725804328918457}],"concepts":[{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6261183619499207},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.6021504402160645},{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.5723250508308411},{"id":"https://openalex.org/C2776247918","wikidata":"https://www.wikidata.org/wiki/Q1423713","display_name":"Structural health monitoring","level":2,"score":0.5681446194648743},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5488201379776001},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5348206162452698},{"id":"https://openalex.org/C108811297","wikidata":"https://www.wikidata.org/wiki/Q214518","display_name":"Admittance","level":3,"score":0.5082442164421082},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4977469742298126},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.48790356516838074},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.484224796295166},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.44681552052497864},{"id":"https://openalex.org/C135628077","wikidata":"https://www.wikidata.org/wiki/Q220184","display_name":"Finite element method","level":2,"score":0.44614121317863464},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.43264010548591614},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4267447590827942},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37667596340179443},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.27204060554504395},{"id":"https://openalex.org/C17829176","wikidata":"https://www.wikidata.org/wiki/Q179043","display_name":"Electrical impedance","level":2,"score":0.2118161916732788},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21069681644439697},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17946496605873108},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17579826712608337},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.14725804328918457},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"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/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tr.2022.3179602","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tr.2022.3179602","pdf_url":null,"source":{"id":"https://openalex.org/S87725633","display_name":"IEEE Transactions on Reliability","issn_l":"0018-9529","issn":["0018-9529","1558-1721"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Reliability","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6037174771","display_name":null,"funder_award_id":"1824761","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"},{"id":"https://openalex.org/G6326218119","display_name":null,"funder_award_id":"1825324","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"}],"funders":[{"id":"https://openalex.org/F4320335353","display_name":"National Science Foundation of Sri Lanka","ror":"https://ror.org/010xaa060"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W133251416","https://openalex.org/W1581422098","https://openalex.org/W1964490787","https://openalex.org/W1967734163","https://openalex.org/W1974937407","https://openalex.org/W2004136766","https://openalex.org/W2016028169","https://openalex.org/W2026757872","https://openalex.org/W2030113781","https://openalex.org/W2040932457","https://openalex.org/W2049387919","https://openalex.org/W2053967096","https://openalex.org/W2054944014","https://openalex.org/W2085137213","https://openalex.org/W2094009285","https://openalex.org/W2106411961","https://openalex.org/W2113741278","https://openalex.org/W2117561707","https://openalex.org/W2131241448","https://openalex.org/W2143672530","https://openalex.org/W2149721706","https://openalex.org/W2156614992","https://openalex.org/W2166566250","https://openalex.org/W2167986580","https://openalex.org/W2192203593","https://openalex.org/W2401855953","https://openalex.org/W2556372419","https://openalex.org/W2577761826","https://openalex.org/W2585874231","https://openalex.org/W2591055632","https://openalex.org/W2612216687","https://openalex.org/W2732547613","https://openalex.org/W2735706443","https://openalex.org/W2756837310","https://openalex.org/W2773031903","https://openalex.org/W2774799914","https://openalex.org/W2781953303","https://openalex.org/W2801712269","https://openalex.org/W2893995718","https://openalex.org/W2950929549","https://openalex.org/W2961523456","https://openalex.org/W2998410485","https://openalex.org/W3004017446","https://openalex.org/W3024753947","https://openalex.org/W3034565885","https://openalex.org/W3035069654","https://openalex.org/W3105216179","https://openalex.org/W3119689123","https://openalex.org/W3184267170","https://openalex.org/W3201680193","https://openalex.org/W3214992126","https://openalex.org/W4234228486","https://openalex.org/W4238746485","https://openalex.org/W4252003911","https://openalex.org/W4286387202","https://openalex.org/W6605391468","https://openalex.org/W6676179485","https://openalex.org/W6677764299","https://openalex.org/W6678911119","https://openalex.org/W6681154564","https://openalex.org/W6684921082","https://openalex.org/W6730269975","https://openalex.org/W6737622681","https://openalex.org/W6755463424","https://openalex.org/W6763801715","https://openalex.org/W6790875989"],"related_works":["https://openalex.org/W2931365531","https://openalex.org/W3014573403","https://openalex.org/W4381941132","https://openalex.org/W2169974588","https://openalex.org/W2084593435","https://openalex.org/W2114881872","https://openalex.org/W3084133043","https://openalex.org/W2139145565","https://openalex.org/W2905297725","https://openalex.org/W2051508398"],"abstract_inverted_index":{"Structural":[0],"health":[1],"monitoring":[2],"(SHM)":[3],"is":[4,98,124],"of":[5,11,51,67,75,121,173],"significant":[6],"importance":[7],"in":[8,108],"the":[9,16,36,52,55,59,63,68,73,76,86,90,102,105,109,118,122,145,171,174],"operation":[10],"engineering":[12],"systems":[13],"to":[14,34,61,100],"ensure":[15],"durability":[17],"and":[18,54,65,94,117,135,140,169],"reliability.":[19],"In":[20],"this":[21],"article,":[22],"we":[23],"introduce":[24],"a":[25,30,44,81,157],"Bayesian":[26,110],"optimization":[27,149],"method":[28,42,71,123,130,155],"using":[29,164],"multioutput":[31,82],"Gaussian":[32,83],"process":[33,84],"solve":[35],"structural":[37,106,160],"fault":[38],"diagnosis":[39,78],"problem.":[40],"This":[41],"utilizes":[43],"high":[45],"fidelity":[46],"finite":[47],"element":[48],"model":[49,88,93],"(FE)":[50],"structure":[53,60],"impedance/admittance":[56],"measurements":[57],"from":[58],"identify":[62],"location":[64],"severity":[66],"damage.":[69],"The":[70,112],"improves":[72],"accuracy":[74],"damage":[77,107,161],"by":[79],"adopting":[80],"as":[85],"surrogate":[87],"for":[89,104],"full":[91],"FE":[92],"Thompson":[95],"sampling":[96],"approach":[97],"used":[99],"guide":[101],"search":[103],"optimization.":[111],"detailed":[113],"algorithms":[114],"are":[115],"presented,":[116],"convergence":[119,142],"analysis":[120],"conducted.":[125],"We":[126,151],"apply":[127,153],"our":[128,154],"proposed":[129,175],"on":[131,156],"simulated":[132],"synthetic":[133],"functions":[134],"it":[136],"achieves":[137],"better":[138],"performance":[139],"higher":[141],"speed":[143],"than":[144],"traditional":[146],"mixed":[147],"input":[148],"methods.":[150],"then":[152],"real":[158],"world":[159],"identification":[162],"problem":[163],"measured":[165],"piezoelectric":[166],"admittance":[167],"data":[168],"illustrate":[170],"effectiveness":[172],"method.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}