Pregled bibliografske jedinice broj: 999298
Detection of Sparse Damages in Structures
Detection of Sparse Damages in Structures // IABSE Symposium 2019 Guimarães - Report / Santos, Luís Oliveira (ur.).
Zürich: International Association for Bridge and Structural Engineering (IABSE), 2019. str. 515-522 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 999298 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Detection of Sparse Damages in Structures
Autori
Sabourova, Natalia ; Grip, Niklas ; Ohlsson, Ulf ; Elfgren, Lennart ; Tu, Yongming ; Duvnjak, Ivan ; Damjanović, Domagoj ;
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
IABSE Symposium 2019 Guimarães - Report
/ Santos, Luís Oliveira - Zürich : International Association for Bridge and Structural Engineering (IABSE), 2019, 515-522
ISBN
978-3-85748-163-5
Skup
IABSE SYMPOSIUM Towards a Resilient Built Environment (GUIMARÃES 2019)
Mjesto i datum
Guimarães, Portugal, 27.03.2019. - 29.03.2019
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
sparse damage ; 𝑙1-norm ; 𝑙2-norm ; total variation ; dictionary-based regularization, sensitivity
Sažetak
Structural damage is often a spatially sparse phenomenon, i.e. it occurs only in a small part of the structure. This property of damage has not been utilized in the field of structural damage identification until quite recently, when the sparsity-based regularization developed in compressed sensing problems found its application in this field. In this paper we consider classical sensitivity-based finite element model updating combined with a regularization technique appropriate for the expected type of sparse damage. Traditionally, (I), 𝑙2- norm regularization was used to solve the ill-posed inverse problems, such as damage identification. However, using already well established, (II), 𝑙1-norm regularization or our proposed, (III), 𝑙1-norm total variation regularization and, (IV), general dictionary-based regularization allows us to find damages with special spatial properties quite precisely using much fewer measurement locations than the number of possibly damaged elements of the structure. The validity of the proposed methods is demonstrated using simulations on a Kirchhoff plate model. The pros and cons of these methods are discussed.
Izvorni jezik
Engleski
Znanstvena područja
Građevinarstvo
POVEZANOST RADA
Ustanove:
Građevinski fakultet, Zagreb