Anisotropic reduction factor-based damage identification method for fiber-reinforced composite laminates

被引:4
作者
Wang, Xiaojun [1 ]
Shi, Qinghe [1 ]
Wang, Lei [1 ]
Lv, Zheng [1 ]
Chen, Xiao [1 ]
Ma, Yujia [1 ]
机构
[1] Beihang Univ, Inst Solid Mech, Beijing 100083, Peoples R China
基金
中国国家自然科学基金;
关键词
composite laminates; damage identification; failure mode; model updating; strain energy; FINITE-ELEMENT MODEL; STRAIN-ENERGY METHOD; MODAL-ANALYSIS; FREQUENCY; ALGORITHM;
D O I
10.1002/stc.2253
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Nowadays, the existing damage detection methods for composite structures roughly identify the defects by equivalent means without considering their anisotropy. Owing to this reason, this article is aimed at proposing an anisotropic reduction factor (ARF)-based damage identification method in view of the description of damage in composite continuum damage mechanics (CDM). On the basis of the proposed method, the adequate damage information including the damage locations, types, and extent will be achieved. The ARF is established referring to the damage model in structures made of isotropic materials utilizing the damage parameter in CDM. To eliminate the dispersion of composite structures, the model updating for the pristine structure is performed. Then a two-step damage identification for detecting the ARF is put forward. First, the modal strain energy-based method is utilized to locate the damage, by which the candidate damaged elements can be selected. Here, taking advantage of the improved reduction system method, the damage localization method can be completed with incomplete modal information. Second, the optimization method based on direct search algorithm is adopted to identify the damage type and extent of the candidate elements by minimizing the error of the modal information between the reference model and the damage model. The measurement noises are taken into consideration. Two numerical examples and an experimental example are studied to demonstrate the effectiveness of the proposed method.
引用
收藏
页数:25
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