A Kriging Model Based Finite Element Model Updating Method for Damage Detection
Model updating is an effective means of damage identification and surrogate modeling has attracted considerable attention for saving computational cost in finite element (FE) model updating, especially for large-scale structures. In this context, a surrogate model of frequency is normally constructe...
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doaj-0dd500fc03ff4cb0975f0eb413e543102020-11-24T23:55:28ZengMDPI AGApplied Sciences2076-34172017-10-01710103910.3390/app7101039app7101039A Kriging Model Based Finite Element Model Updating Method for Damage DetectionXiuming Yang0Xinglin Guo1Huajiang Ouyang2Dongsheng Li3Department of Engineering Mechanics, State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116000, ChinaDepartment of Engineering Mechanics, State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116000, ChinaDepartment of Engineering Mechanics, State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116000, ChinaSchool of Civil Engineering, Dalian University of Technology, Dalian 116000, ChinaModel updating is an effective means of damage identification and surrogate modeling has attracted considerable attention for saving computational cost in finite element (FE) model updating, especially for large-scale structures. In this context, a surrogate model of frequency is normally constructed for damage identification, while the frequency response function (FRF) is rarely used as it usually changes dramatically with updating parameters. This paper presents a new surrogate model based model updating method taking advantage of the measured FRFs. The Frequency Domain Assurance Criterion (FDAC) is used to build the objective function, whose nonlinear response surface is constructed by the Kriging model. Then, the efficient global optimization (EGO) algorithm is introduced to get the model updating results. The proposed method has good accuracy and robustness, which have been verified by a numerical simulation of a cantilever and experimental test data of a laboratory three-story structure.https://www.mdpi.com/2076-3417/7/10/1039model updatingfrequency response functionKriging modeldamage detection |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiuming Yang Xinglin Guo Huajiang Ouyang Dongsheng Li |
spellingShingle |
Xiuming Yang Xinglin Guo Huajiang Ouyang Dongsheng Li A Kriging Model Based Finite Element Model Updating Method for Damage Detection Applied Sciences model updating frequency response function Kriging model damage detection |
author_facet |
Xiuming Yang Xinglin Guo Huajiang Ouyang Dongsheng Li |
author_sort |
Xiuming Yang |
title |
A Kriging Model Based Finite Element Model Updating Method for Damage Detection |
title_short |
A Kriging Model Based Finite Element Model Updating Method for Damage Detection |
title_full |
A Kriging Model Based Finite Element Model Updating Method for Damage Detection |
title_fullStr |
A Kriging Model Based Finite Element Model Updating Method for Damage Detection |
title_full_unstemmed |
A Kriging Model Based Finite Element Model Updating Method for Damage Detection |
title_sort |
kriging model based finite element model updating method for damage detection |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2017-10-01 |
description |
Model updating is an effective means of damage identification and surrogate modeling has attracted considerable attention for saving computational cost in finite element (FE) model updating, especially for large-scale structures. In this context, a surrogate model of frequency is normally constructed for damage identification, while the frequency response function (FRF) is rarely used as it usually changes dramatically with updating parameters. This paper presents a new surrogate model based model updating method taking advantage of the measured FRFs. The Frequency Domain Assurance Criterion (FDAC) is used to build the objective function, whose nonlinear response surface is constructed by the Kriging model. Then, the efficient global optimization (EGO) algorithm is introduced to get the model updating results. The proposed method has good accuracy and robustness, which have been verified by a numerical simulation of a cantilever and experimental test data of a laboratory three-story structure. |
topic |
model updating frequency response function Kriging model damage detection |
url |
https://www.mdpi.com/2076-3417/7/10/1039 |
work_keys_str_mv |
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1725462338545385472 |