A sensor-based calibration system for three-dimensional digital image correlation
A sensor-based calibration system for three-dimensional digital image correlation
复制标题
基于传感器的三维数字图像相关校准系统
DOI：
10.1117/12.2612106
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Sabato, Alessandro
中科院分区：
文献类型：
--
作者：
Bottalico, Fabio;Valente, Nicholas A.;Dabetwar, Shweta;Jerath, Kshitij;Luo, Yan;Niezrecki, Christopher;Sabato, Alessandro
三维数字图像相关（3D-DIC）已成为结构健康监测的传统接触式技术的有力替代品。3D-DIC可以从一组同步的立体图像中提取结构的全场位移。在执行3D-DIC之前，必须完成复杂的校准过程以获得立体视觉系统的外部参数（即，相机的距离和方向）。校准所需的时间取决于目标结构的尺寸。例如，对于大型结构，校准可能需要几个小时。此外，每当相机的位置改变时，需要新的校准来重新计算外部参数。在这项研究中提出的方法允许确定的3D-DIC外部参数，使用市售传感器测量的数据。该系统利用三个惯性测量单元和一个激光测距仪来计算相机之间的相对方位和距离。在本文中，新开发的传感器套件的灵敏度的评估提供了评估的外部参数的测量误差。使用从传感器检索的数据在7.5 x 5.7 m视场上进行的分析模拟表明，所提出的方法提供了~10-6 m的精度，并且是降低3D-DIC校准复杂性的有前途的方法。
Three-dimensional digital image correlation (3D-DIC) has become a strong alternative to traditional contact-based techniques for structural health monitoring. 3D-DIC can extract the full-field displacement of a structure from a set of synchronized stereo images. Before performing 3D-DIC, a complex calibration process must be completed to obtain the stereovision system’s extrinsic parameters (i.e., cameras’ distance and orientation). The time required for the calibration depends on the dimensions of the targeted structure. For example, for large-scale structures, the calibration may take several hours. Furthermore, every time the cameras’ position changes, a new calibration is required to recalculate the extrinsic parameters. The approach proposed in this research allows determining the 3D-DIC extrinsic parameters using the data measured with commercially available sensors. The system utilizes three Inertial Measurement Units with a laser distance meter to compute the relative orientation and distance between the cameras. In this paper, an evaluation of the sensitivity of the newly developed sensor suite is provided by assessing the errors in the measurement of the extrinsic parameters. Analytical simulations performed on a 7.5 x 5.7 m field of view using the data retrieved from the sensors show that the proposed approach provides an accuracy of ~10-6 m and a promising way to reduce the complexity of 3D-DIC calibration.