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通过冲击锤模态测试和实验验证对钢-混凝土组合结构进行损伤检测

Damage Detection in Steel-Concrete Composite Structures by Impact Hammer Modal Testing and Experimental Validation.

作者信息

Meruane Viviana, Yanez Sergio J, Quinteros Leonel, Saavedra Flores Erick I

机构信息

Department of Mechanical Engineering, Universidad de Chile, Beauchef 851, Santiago 8370456, Chile.

Civil Engineering Department, University of Santiago of Chile, Av. Víctor Jara 3659, Santiago 8990000, Chile.

出版信息

Sensors (Basel). 2022 May 20;22(10):3874. doi: 10.3390/s22103874.

DOI:10.3390/s22103874
PMID:35632283
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9148021/
Abstract

Steel-concrete composite systems are an efficient alternative to mid- and high-rise building structures because of their high strength-to-weight ratio when compared to traditional concrete or steel constructive systems. Nevertheless, composite structural systems are susceptible to damage due to, for example, deficient construction processes, errors in design and detailing, steel corrosion, and the drying shrinkage of concrete. As a consequence, the overall strength of the structure may be significantly decreased. In view of the relevance of this subject, the present paper addresses the damage detection problem in a steel-concrete composite structure with an impact-hammer-based modal testing procedure. The mathematical formulation adopted in this work allows for the identification of regions where stiffness varies with respect to an initial virgin state without the need for theoretical models of the undamaged structure (such as finite element models). Since mode shape curvatures change due to the loss of stiffness at the presence of cracks, a change in curvature was adopted as a criterion to quantify stiffness reduction. A stiffness variability index based on two-dimensional mode shape curvatures is generated for several points on the structure, resulting in a damage distribution pattern. Our numerical predictions were compared with experimentally measured data in a full-scale steel-concrete composite beam subjected to bending and were successfully validated. The present damage detection strategy provides further insight into the failure mechanisms of steel-concrete composite structures, and promotes the future development of safer and more reliable infrastructures.

摘要

钢-混凝土组合结构体系是中高层建筑结构的一种高效替代方案,因为与传统混凝土或钢结构体系相比,它们具有较高的强度重量比。然而,组合结构体系容易受到损坏,例如施工过程不完善、设计和细节错误、钢材腐蚀以及混凝土干燥收缩等。因此,结构的整体强度可能会显著降低。鉴于该主题的相关性,本文采用基于冲击锤的模态测试程序,研究钢-混凝土组合结构中的损伤检测问题。本研究采用的数学公式允许识别刚度相对于初始未受损状态发生变化的区域,而无需未受损结构的理论模型(如有限元模型)。由于在出现裂缝时刚度损失会导致振型曲率发生变化,因此采用曲率变化作为量化刚度降低的标准。基于二维振型曲率为结构上的多个点生成刚度变异性指标,从而得到损伤分布模式。我们将数值预测结果与一根承受弯曲的全尺寸钢-混凝土组合梁的实验测量数据进行了比较,并成功得到验证。目前的损伤检测策略为钢-混凝土组合结构的破坏机制提供了进一步的见解,并推动了更安全、更可靠基础设施的未来发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/5e0b5e633e6a/sensors-22-03874-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/11111d2a225f/sensors-22-03874-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/89dbb087ec19/sensors-22-03874-g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/f7e91edc80bc/sensors-22-03874-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/ee3ac778286a/sensors-22-03874-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/8150f9f8b839/sensors-22-03874-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/c5a1c0b0a8c7/sensors-22-03874-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/ca64a2ffc627/sensors-22-03874-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/9f1a549ef991/sensors-22-03874-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/511165ccca07/sensors-22-03874-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/d8e91b5d10c2/sensors-22-03874-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/216fce95fba8/sensors-22-03874-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/5e0b5e633e6a/sensors-22-03874-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/11111d2a225f/sensors-22-03874-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/89dbb087ec19/sensors-22-03874-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/459919e58e30/sensors-22-03874-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/8d53931fc3d5/sensors-22-03874-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/f7e91edc80bc/sensors-22-03874-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/ee3ac778286a/sensors-22-03874-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/8150f9f8b839/sensors-22-03874-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/c5a1c0b0a8c7/sensors-22-03874-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/ca64a2ffc627/sensors-22-03874-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/9f1a549ef991/sensors-22-03874-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/511165ccca07/sensors-22-03874-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/d8e91b5d10c2/sensors-22-03874-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/216fce95fba8/sensors-22-03874-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b04/9148021/5e0b5e633e6a/sensors-22-03874-g014.jpg

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