Comparison of ABC, CPSO, DE and GA algorithms in FRF based structural damage identification

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dc.contributor.buuauthorGökdaǧ, Hakan
dc.contributor.departmentUludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.tr_TR
dc.contributor.orcid0000-0003-3070-6365tr_TR
dc.contributor.researcheridF-3233-2016tr_TR
dc.contributor.scopusid23012197200tr_TR
dc.date.accessioned2023-05-30T11:06:24Z
dc.date.available2023-05-30T11:06:24Z
dc.date.issued2013
dc.description.abstractIn this contribution, performances of well-known population based algorithms, the artificial bee colony (ABC), contemporary particle swarm optimization (CPSO), genetic algorithm (GA), and differential evolution (DE) are compared in a basic model for damage identification (DI). DI is modeled as an inverse problem with the objective function based on the difference of the frequency response functions (FRF) computed by the finite element model of the structure and the reference data measured from damaged structure. Damage parameters are determined solving the problem with the aforementioned algorithms. It was observed that DE is the best one of a given number of function evaluations and gives the most accurate results in spite of noise interference to the reference data. According to the relevant literature, this is the first study including a comparison of these algorithms in an FRF based DI study.en_US
dc.identifier.citationGökdağ, H. (2013). “Comparison of ABC, CPSO, DE and GA algorithms in FRF based structural damage identification”. Materials Testing, 55(10), 796-802.en_US
dc.identifier.endpage802tr_TR
dc.identifier.issn0025-5300
dc.identifier.issue10tr_TR
dc.identifier.scopus2-s2.0-84886511829tr_TR
dc.identifier.startpage796tr_TR
dc.identifier.urihttps://doi.org/10.3139/120.110503
dc.identifier.urihttps://www.degruyter.com/document/doi/10.3139/120.110503/html
dc.identifier.urihttp://hdl.handle.net/11452/32882
dc.identifier.volume55tr_TR
dc.identifier.wos000327005400011tr_TR
dc.indexed.scopusScopusen_US
dc.indexed.wosSCIEen_US
dc.language.isoenen_US
dc.publisherWalter De Gruyterde
dc.relation.journalMaterials Testingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergitr_TR
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMaterials scienceen_US
dc.subjectParticle swarmen_US
dc.subjectDifferential evolutionen_US
dc.subjectCrack detectionen_US
dc.subjectFrequencyen_US
dc.subjectDamage detectionen_US
dc.subjectFinite element methoden_US
dc.subjectFrequency responseen_US
dc.subjectGenetic algorithmsen_US
dc.subjectInverse problemsen_US
dc.subjectOptimizationen_US
dc.subjectParticle swarm optimization (PSO)en_US
dc.subjectStructural analysisen_US
dc.subjectArtificial bee colonies (ABC)en_US
dc.subjectDamage identificationen_US
dc.subjectDifferential evolutionen_US
dc.subjectFrequency response functionsen_US
dc.subjectNoise interferenceen_US
dc.subjectObjective functionsen_US
dc.subjectPopulation-based algorithmen_US
dc.subjectStructural damage identificationen_US
dc.subjectEvolutionary algorithmsen_US
dc.subject.scopusDamage Identification; Mode Shape; Structural Analysisen_US
dc.subject.wosMaterials science, characterization & testingen_US
dc.titleComparison of ABC, CPSO, DE and GA algorithms in FRF based structural damage identificationen_US
dc.typeArticle
dc.wos.quartileQ4en_US

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