桥梁结构连续线形监测方法

A Monitoring Method for Continuous Line-shape of Bridge Structure

为解决因桥梁测点有限导致结构安全状态评价困难的问题,基于数字图像对结构形态的全场描述能力提出了一种基于桥梁图像边缘特征点的连续线形监测方法。在实验室制作了长7 m的钢-桁混凝土组合梁试件,获取了不同工况下试验梁的数字图像。通过尺度不变特征变换算法(SIFT)提取了试验梁图像的特征点,发现了试验梁图像特征存在局部边缘特征不连续、像素缺失的问题。采用了灰度形态学理论对图像进行处理,通过灰度形态学的开运算与闭运算连接了试验梁图像的边缘断点,改善了试验梁图像边缘特征的连续性。提出了一种基于桥梁已知构件尺寸的图像监测分辨率标定方法,对图像的像素尺寸进行了标定,得到了试验梁图像的监测分辨率。提取了试验梁下部边缘线形,发现不同工况下结构的边缘线形受噪声影响呈现相似的规律性的震荡,提出了一种叠差分析方法对含噪边缘进行处理,得到了连续平滑的试验梁挠度曲线。结果表明:挠度曲线最大误差为4.92%,平均误差为2.09%。该方法首次在自然纹理条件下实现了桥梁连续线形监测,将传统结构单点监测扩展至连续线形监测,显著提升了监测数据的完备性。研究成果可为桥梁经常性安全监测及诊断提供经济有效的新方法。

In order to solve the problem of difficult structural safety state evaluation due to the limited measuring points of bridges,based on the full-field description ability of digital image to structure shape,a continuous line-shape monitoring method based on edge feature points of bridge image is proposed.A 7 mlong steel-truss concrete composite beam specimen is made in the laboratory,and the digital images of the test beams under different working conditions are obtained.The feature points of the experimental beam image are extracted by scale-invariant feature transform(SIFT)algorithm,and it is found that the local edge features of the experimental beam image are discontinuous and the pixels are missing.The gray-scale morphology theory is used to process the image,and the edge breakpoints of the test beam image are connected by the open and closed operation of gray-scale morphology,which improves the continuity of the edge features of the test beam image.A method for calibrating the image monitoring resolution based on the known component size of bridge is proposed,the pixel size of the image is calibrated,and the monitoring resolution of the experimental beam image is obtained.The lower edge profile of the test beam is extracted,and it is found that the edge profile of the structure under different working conditions shows similar regular oscillation under the influence of noise,the continuous and smooth deflection curves of the test beam are obtained.The result shows that the maximum error of deflection curve is 4.92%and the average error is 2.09%.It is the first time to realize continuous line-shape monitoring of bridge under natural texture condition,that extends traditional single-point monitoring to continuous line-shape monitoring,and improves the completeness of monitoring data.The study result can provide a new method for frequent safety monitoring and diagnosis of bridges.