Comparison of ABC, CPSO, DE and GA Algorithms in FRF Based Structural Damage Identification
Küçük Resim Yok
Tarih
2013
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Carl Hanser Verlag
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In 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.
Açıklama
Anahtar Kelimeler
[No Keywords]
Kaynak
Materials Testing
WoS Q Değeri
Q4
Scopus Q Değeri
Q2
Cilt
55
Sayı
10
