Zheng Wenting, Xu Bin, Xia Zongjun, Wang Jiang, Liu Jingliang, Yao Yudi, Wang Yifei
College of Civil Engineering, Huaqiao University, Xiamen 361021, China.
College of Civil Engineering, Fujian University of Technology, Fuzhou 350118, China.
Sensors (Basel). 2024 Apr 13;24(8):2503. doi: 10.3390/s24082503.
Concrete-filled steel tube (CFST) members have been widely used in civil engineering due to their advanced mechanical properties. However, internal defects such as the concrete core voids and interface debonding in CFST structures are likely to weaken their load-carrying capacity and stiffness, which affects the safety and serviceability. Visualizing the inner defects of the concrete cores in CFST members is a critical requirement and a challenging task due to the obvious difference in the material mechanical parameters of the concrete core and steel tube in CFST members. In this study, a curved ray theory-based travel time tomography (TTT) with a least square iterative linear inversion algorithm is first introduced to quantitatively identify and visualize the sizes and positions of the concrete core voids in CFST members. Secondly, a numerical investigation of the influence of different parameters on the inversion algorithm for the defect imaging of CFST members, including the effects of the model weighting matrix, weighting factor and grid size on the void's imaging quality and accuracy, is carried out. Finally, an experimental study on six CFST specimens with mimicked concrete core void defects is performed in a laboratory and the mimicked defects are visualized. The results demonstrate that TTT can identify the sizes and positions of the concrete core void defects in CFST members efficiently with the use of optimal parameters.
钢管混凝土(CFST)构件因其优异的力学性能而在土木工程中得到广泛应用。然而,CFST结构内部的缺陷,如混凝土芯部空洞和界面脱粘,可能会削弱其承载能力和刚度,进而影响结构的安全性和适用性。由于CFST构件中混凝土芯部和钢管的材料力学参数存在明显差异,可视化CFST构件中混凝土芯部的内部缺陷是一项关键要求且极具挑战性。在本研究中,首先引入基于弯曲射线理论的走时层析成像(TTT)方法及最小二乘迭代线性反演算法,以定量识别和可视化CFST构件中混凝土芯部空洞的尺寸和位置。其次,对不同参数对CFST构件缺陷成像反演算法的影响进行了数值研究,包括模型加权矩阵、加权因子和网格尺寸对空洞成像质量和精度的影响。最后,在实验室对六个模拟混凝土芯部空洞缺陷的CFST试件进行了试验研究,并对模拟缺陷进行了可视化。结果表明,利用最优参数,TTT能够有效地识别CFST构件中混凝土芯部空洞缺陷的尺寸和位置。