光场单相机三维流场测试技术

丁俊飞; 许晟明; 施圣贤

doi:10.11729/syltlx20160141

光场单相机三维流场测试技术

上海交通大学机械与动力工程学院燃气轮机研究院, 上海 200240

基金项目:

国家自然科学基金 11472175

上海市启明星项目 15QA1402400

详细信息

作者简介:
丁俊飞(1992-), 男, 山西太原人, 博士研究生。研究方向:三维流体测量。通信地址:上海交通大学机械与动力工程学院燃气轮机研究院(200240)。E-mail:junfeiding@sjtu.edu.cn

通讯作者:
施圣贤, E-mail:kirinshi@sjtu.edu.cn

中图分类号: V211.71
计量
- 文章访问数: 373
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出版历程
- 收稿日期: 2016-09-17
- 修回日期: 2016-10-12
- 刊出日期: 2016-12-24

Light field volumetric particle image velocimetry

Gas Turbine Research Institute, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

摘要

摘要: 将光场三维成像技术与实验流体力学相结合，实现单相机对空间三维瞬态流场（3D3C）的精确测量，为流体力学实验研究提供了一种全新的测试技术。详细介绍了具有自主知识产权的光场相机硬件系统、基于乘积代数重建技术（MART）的粒子光场图像重构算法以及基于光线追迹的数字光场图像合成算法。利用DNS数字合成图像以及低速射流实验图像，将所发展的光场单相机三维流场测试技术（Light Field Particle Image Velocimetry，LF-PIV）与目前最成熟的三维流场测试技术层析PIV（Tomographic Particle Image Velocimetry，Tomo-PIV）进行对比研究分析。实验结果表明LF-PIV技术完全能达到与Tomo-PIV同等量级的测量精度。
- 光场PIV /
- 光场相机 /
- 单相机三维PIV /
- 层析PIV
Abstract: A novel single camera volumetric velocity measurement technique is presented, which utilizes the advanced light field imaging technology to capture 3D PIV tracer particle images. The framework of Light Field Particle Image Velocimetry (LF-PIV) includes an in-house high resolution light field camera, multiplicative algebraic reconstruction technique (MART) based light field particle image reconstruction method and a ray tracing based synthetic light field particle image generation platform. The LF-PIV technique is compared with Tomographic Particle Image Velocimetry (Tomo-PIV) by using both synthetic DNS jet flow images as well as water jet experimental images. Results show that LF-PIV is capable of reconstructing the instantaneous volumetric velocity field with the accuracy similar to that of Tomo-PIV.
- Light Field PIV /
- light field camera /
- single camera volumetric PIV /
- Tomo-PIV

HTML全文

图 1 光场的2种参数化表示方式^[29]

Fig. 1 Two methods of light field parameterisation

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图 2 光场相机原理示意图及光线追迹原理示意图^{[26, 28]}

Fig. 2 Schematics of light field camera and ray tracing method

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图 3 自主光场相机系统

Fig. 3 In-house light field camera system

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图 4 原始光场图片及光场渲染效果

Fig. 4 Raw light field image and results of refocusing and perspective shift processing

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图 5 基于密集光线追迹的权重系数算法原理示意图^{[26, 28]}

Fig. 5 Schematics of ray tracing based weighting coefficient method

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图 6 对比仿真分析结果

Fig. 6 Simulation results

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图 7 LF-PIV和Tomo-PIV的测量误差

Fig. 7 Measurement error of LF-PIV and Tomo-PIV

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图 8 LF-PIV、Tomo-PIV同步测试实验系统实物图

Fig. 8 Experimental setup of LF-PIV and Tomo-PIV system

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图 9 实验粒子光场图像局部放大图

Fig. 9 Real light field particle image (zoom in)

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图 10 实验三维瞬态速度场

Fig. 10 Instantaneous velocity fields

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表 1 用于产生数字合成光场图像的光学参数数值

Table 1 Parameters for generating synthetic light field images

符号	意义	相机参数	合成图像参数
n_lx	MLA x方向分辨率	410	410
n_ly	MLA y方向分辨率	310	310
p_l	微透镜单元直径	77μm	77μm
f_l	微透镜焦距	310μm	310μm
n_px	相机x方向分辨率	6600pixel	6600pixel
n_py	相机y方向分辨率	4400pixel	4400pixel
p_p	像素直径	5.5μm	5.5μm
f_m	主镜头焦距	-	50mm
p_m	主镜头孔径	-	25mm
S_o	物距	-	100mm
S_l	相距	-	100mm
M	放大系数	-	-1
(f/#)_m	主镜头f数	-	2
(f/#)_l	微透镜f数	-	4

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