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A Novel Stochastic Approach for Static Damage Identification of Beam Structures Using Homotopy Analysis Algorithm
This paper proposes a new damage identification approach for beam structures with stochastic parameters based on uncertain static measurement data. This new approach considers not only the static measurement errors, but also the modelling error of the initial beam structures as random quantities, an...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8037578/ https://www.ncbi.nlm.nih.gov/pubmed/33805366 http://dx.doi.org/10.3390/s21072366 |
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author | Wu, Zhifeng Huang, Bin Tee, Kong Fah Zhang, Weidong |
author_facet | Wu, Zhifeng Huang, Bin Tee, Kong Fah Zhang, Weidong |
author_sort | Wu, Zhifeng |
collection | PubMed |
description | This paper proposes a new damage identification approach for beam structures with stochastic parameters based on uncertain static measurement data. This new approach considers not only the static measurement errors, but also the modelling error of the initial beam structures as random quantities, and can also address static damage identification problems with relatively large uncertainties. First, the stochastic damage identification equations with respect to the damage indexes were established. On this basis, a new homotopy analysis algorithm was used to solve the stochastic damage identification equations. During the process of solution, a static condensation technique and a L1 regularization method were employed to address the limited measurement data and ill-posed problems, respectively. Furthermore, the definition of damage probability index is presented to evaluate the possibility of existing damages. The results of two numerical examples show that the accuracy and efficiency of the proposed damage identification approach are good. In comparison to the first-order perturbation method, the proposed method can ensure better accuracy in damage identification with relatively large measurement errors and modelling error. Finally, according to the static tests of a simply supported concrete beam, the proposed method successfully identified the damage of the beam. |
format | Online Article Text |
id | pubmed-8037578 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-80375782021-04-12 A Novel Stochastic Approach for Static Damage Identification of Beam Structures Using Homotopy Analysis Algorithm Wu, Zhifeng Huang, Bin Tee, Kong Fah Zhang, Weidong Sensors (Basel) Article This paper proposes a new damage identification approach for beam structures with stochastic parameters based on uncertain static measurement data. This new approach considers not only the static measurement errors, but also the modelling error of the initial beam structures as random quantities, and can also address static damage identification problems with relatively large uncertainties. First, the stochastic damage identification equations with respect to the damage indexes were established. On this basis, a new homotopy analysis algorithm was used to solve the stochastic damage identification equations. During the process of solution, a static condensation technique and a L1 regularization method were employed to address the limited measurement data and ill-posed problems, respectively. Furthermore, the definition of damage probability index is presented to evaluate the possibility of existing damages. The results of two numerical examples show that the accuracy and efficiency of the proposed damage identification approach are good. In comparison to the first-order perturbation method, the proposed method can ensure better accuracy in damage identification with relatively large measurement errors and modelling error. Finally, according to the static tests of a simply supported concrete beam, the proposed method successfully identified the damage of the beam. MDPI 2021-03-29 /pmc/articles/PMC8037578/ /pubmed/33805366 http://dx.doi.org/10.3390/s21072366 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ). |
spellingShingle | Article Wu, Zhifeng Huang, Bin Tee, Kong Fah Zhang, Weidong A Novel Stochastic Approach for Static Damage Identification of Beam Structures Using Homotopy Analysis Algorithm |
title | A Novel Stochastic Approach for Static Damage Identification of Beam Structures Using Homotopy Analysis Algorithm |
title_full | A Novel Stochastic Approach for Static Damage Identification of Beam Structures Using Homotopy Analysis Algorithm |
title_fullStr | A Novel Stochastic Approach for Static Damage Identification of Beam Structures Using Homotopy Analysis Algorithm |
title_full_unstemmed | A Novel Stochastic Approach for Static Damage Identification of Beam Structures Using Homotopy Analysis Algorithm |
title_short | A Novel Stochastic Approach for Static Damage Identification of Beam Structures Using Homotopy Analysis Algorithm |
title_sort | novel stochastic approach for static damage identification of beam structures using homotopy analysis algorithm |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8037578/ https://www.ncbi.nlm.nih.gov/pubmed/33805366 http://dx.doi.org/10.3390/s21072366 |
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