Back to Search Start Over

Residual Mode Vector-Based Structural Damage Identification with First-Order Modal Information

Authors :
Shuai Luo
Zhenxin Zhuang
Wei Wang
Ping Jiang
Source :
Advances in Materials Science and Engineering, Vol 2021 (2021)
Publication Year :
2021
Publisher :
Hindawi Limited, 2021.

Abstract

Damage identification based on the change of dynamic properties is an issue worthy of attention in structure safety assessment, nevertheless, only a small number of discontinuous members in existing structure are damaged under service condition, and the most remaining members are in good condition. According to this feather, we developed an effective damage location and situation assessment algorithm based on residual mode vector with the first mode information of targeted structure, which utilized the quantitative relationship between first natural modes of global structure with the change of the element stiffness. Firstly, the element damage location is determined with exploitation of the sparseness of element stiffness matrices based on the discontinuity of damaged members. Then, according to the distribution characteristics of the corresponding residual mode vector, the nodal equilibrium equation about the damage parameter is established based on the residual mode vector, and the damage coefficients of structural elements are evaluated with the proposed equations. Two numerical examples are given to verify the proposed algorithm. The results showed that the proposed damage identification method is consistent with the preset damage. It can even accurately identify large-degree damages. The proposed algorithm only required the first-order modal information of the target structures and held few requirements of analysis resource; hence when compared with existing methods, it has obvious advantages for structural damage identification.

Details

Language :
English
ISSN :
16878434 and 16878442
Volume :
2021
Database :
Directory of Open Access Journals
Journal :
Advances in Materials Science and Engineering
Publication Type :
Academic Journal
Accession number :
edsdoj.3113be5fd8bd454dab1085c4c1b46b24
Document Type :
article
Full Text :
https://doi.org/10.1155/2021/5526171