Infrared Thermography-based Void Detection Technology for Concrete-filled Steel Tubes
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摘要: 钢管混凝土结构因受施工工艺、混凝土收缩、超负荷承载等因素而产生脱空缺陷,使结构的承载能力下降。本文利用主动热成像技术对钢管混凝土的脱空缺陷进行了研究,并针对当前热成像脱空检测技术存在检测深度小,处理算法呈现效果不佳,无法定量检测,检测效率低等问题,提出了设计专用感应加热电源和线盘提高检测深度,热源反演算法消除加热非均匀性干扰,建立无缺陷仿真模型预测钢管混凝土表面的温度分布,取同一时刻的实验数据和仿真预测数据作差来提取脱空缺陷特征,以及检测参数优化实现定量检测的解决方法。通过多次重复实验表明,可检出壁厚为20 mm钢管混凝土内的脱空缺陷,并能确定缺陷形状和大小,有效提高了检测深度和检测效率。Abstract: The concrete-filled steel tube structure has void defects owing to factors such as construction technology, concrete shrinkage, and overload bearing, which reduce the load-bearing capacity of the structure. Furthermore, the current thermal imaging based void detection technology has a small detection depth, poor processing algorithm rendering effect, inability to detect quantitatively, and low detection efficiency. In this study, an active thermal imaging technology was used to study the void defects of concrete-filled steel tubes. A special induction heating power supply and heating probe are designed to increase the detection depth, and a heat source inversion algorithm eliminates the heating non-uniformity interference. In addition, a defect-free simulation model is established to predict the temperature distribution of the concrete-filled steel tube surface. Moreover, the difference between the experimental data and the simulation prediction data was obtained to extract the characteristics of the void defect and optimize the detection parameters to realize a quantitative detection solution. Through repeated experiments, it was shown that void defects in concrete-filled steel tubes with a wall thickness of 20mm can be detected, and the shape and size of the defects can be determined, which effectively improves the inspection depth and efficiency.
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表 1 材料的物性参数
Table 1. Material parameters
Material Thermal conductivity/
W·m-1·K-1Specific heat
capacity/
J·kg-1·K-1Density/
kg·m-3Steel 49.8 465 7840 Concrete(c30) 1.28 970 2410 Air 0.0259 1005 1.205 -
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