将光场成像理论与三维颗粒追踪测速(PTV)技术相结合,实现了单相机三维流场的测量。结合高斯光学和相似原理,推导出了深度与最优重聚焦系数的关系。搭建了光场标定与流场测量系统,提出基于光场成像理论模型的深度标定方法,并与泰勒多项式拟合方法进行对比,证明了其具有较高的稳健性。利用清晰度最大原理,获得原始光场图像的全聚焦图,采用最小特征值角点检测算法对全聚焦图上的颗粒进行定位,结合三维粒子追踪技术,得到颗粒的三维速度。形成了光场PTV的图像处理流程,并对后向台阶流场进行了实测,结果表明光场PTV技术能够较好地测量三维流场。

In this study, light field imaging theory and three-dimensional (3D) particle tracking velocimetry (PTV) are combined to evaluate a 3D flow field using a single camera. Further, a relation is derived between the depth and the optimal refocusing coefficient based on the Gaussian optics and the similarity principle. Subsequently, the light field calibration and flow field measurement systems are established. A depth calibration method is proposed based on the theoretical model of light field imaging. When compared with the Taylor polynomial fitting method, the proposed method is proved to have high robustness. An all-in-focus image is obtained based on the principle of maximum sharpness. The particles in the all-in-focus image are positioned using the corner detection algorithm based on the minimum eigenvalue; further, the 3D velocities of the particles are obtained using the 3D PTV technology. A processing flow is established for the light field images and applied to the flow field measurement on a back step. The results prove that the light-field-imaging-based PTV technology can reconstruct the volumetric flow field.