光学 精密工程, 2017, 25 (3): 555, 网络出版: 2017-04-18
基于激光扫描的密集泡状流三维重建与优化
3D reconstruction and optimization of dense bubbly flow based on laser scanning
光学三维测量 激光扫描 密集泡状流 三维重建 模板卷积 含气率 optical three-dimensional measurement laser scanning dense bubbly flow three-dimensional reconstruction template convolution void fraction
摘要
为测量密集气液泡状流的流动形态及参数, 建立了基于激光扫描的三维可视化测量系统。采用片状激光结合旋转正多边形棱镜实现对流场的光学扫描, 高速摄像机采集扫描切片图像, 首先对图像进行预处理。针对扫描成像中产生的切片重复曝光问题, 提出二阶微分平均卷积优化算法, 该方法不仅可以有效提取多切片图像中重复曝光的特征点, 而且可以去除冗余及噪声信息。实验结果表明, 针对分散相遮挡的密集泡状流, 基于激光扫描可完整重建其三维结构, 二阶微分优化算法可以有效降低重建畸变影响, 重建后体积含气率的相对误差优于6%。激光扫描方法非侵入、重建精度高, 具有传统方法不可比拟的优势。
Abstract
In order to reconstruct the flow regime of dense bubbly flow and to measure flow parameters, a 3D visual measurement system based on laser scanning was constructed. Laser sheet combined with a rotating polygonal prism was employed for optical scanning of the flow field. The slice images of field were recorded by a high-speed camera and the 3D structure was reconstructed by a series of image preprocessing methods. Considering the multiple exposure in slices during the scanning process, an optimization algorithm based on template convolution of second-order differential and mean was proposed, which can effectively extract feature points of multiple exposure from slices and simultaneously remove redundant and noise information. The experiment results demonstrated that the 3D structure of dense bubbly flow with overlapped projection of bubbles can be perfectly reconstructed by the proposed laser scanning method. The optimization algorithm based on second-order differential can effectively reduce the distortion of reconstructed structure. The volume void fraction of reconstructed field is less than 6% in relative error compared to the actual value. The non-intrusive measurement based on laser scanning can realize 3D reconstruction of the dense bubbly flow with high accuracy, thus proving remarkable advantages in comparison with traditional methods.
薛婷, 阮维鹏, 张少杰. 基于激光扫描的密集泡状流三维重建与优化[J]. 光学 精密工程, 2017, 25(3): 555. XUE Ting, RUAN Wei-peng, ZHANG Shao-jie. 3D reconstruction and optimization of dense bubbly flow based on laser scanning[J]. Optics and Precision Engineering, 2017, 25(3): 555.