An efficient simultaneous reconstruction technique for tomographic particle image velocimetry

被引:14
作者
Callum Atkinson
Julio Soria
机构
[1] Monash University,Laboratory for Turbulence Research in Aerospace and Combustion, Department of Mechanical and Aerospace Engineering
来源
Experiments in Fluids | 2009年 / 47卷
关键词
Weighting Matrix; Turbulent Boundary Layer; Reconstruction Quality; Algebraic Reconstruction Technique; Ghost Particle;
D O I
暂无
中图分类号
学科分类号
摘要
To date, Tomo-PIV has involved the use of the multiplicative algebraic reconstruction technique (MART), where the intensity of each 3D voxel is iteratively corrected to satisfy one recorded projection, or pixel intensity, at a time. This results in reconstruction times of multiple hours for each velocity field and requires considerable computer memory in order to store the associated weighting coefficients and intensity values for each point in the volume. In this paper, a rapid and less memory intensive reconstruction algorithm is presented based on a multiplicative line-of-sight (MLOS) estimation that determines possible particle locations in the volume, followed by simultaneous iterative correction. Reconstructions of simulated images are presented for two simultaneous algorithms (SART and SMART) as well as the now standard MART algorithm, which indicate that the same accuracy as MART can be achieved 5.5 times faster or 77 times faster with 15 times less memory if the processing and storage of the weighting matrix is considered. Application of MLOS-SMART and MART to a turbulent boundary layer at Reθ = 2200 using a 4 camera Tomo-PIV system with a volume of 1,000 × 1,000 × 160 voxels is discussed. Results indicate improvements in reconstruction speed of 15 times that of MART with precalculated weighting matrix, or 65 times if calculation of the weighting matrix is considered. Furthermore the memory needed to store a large weighting matrix and volume intensity is reduced by almost 40 times in this case.
引用
收藏
页码:553 / 568
页数:15
相关论文
共 36 条
[31]   Three-dimensional image reconstruction in projection-based magnetic particle imaging [J].
Murase, Kenya .
JAPANESE JOURNAL OF APPLIED PHYSICS, 2021, 60 (08)
[32]   Introducing a novel fast algebraic reconstruction technique and advancing 3D image reconstruction in a specialized bioimaging system [J].
Polat, Adem .
BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2024, 88
[33]   A new method for extracting spanwise vortex from 2D particle image velocimetry data in open-channel flow [J].
Zhang, Peng ;
Yang, Shengfa ;
Hu, Jiang ;
Li, Wenjie ;
Fu, Xuhui ;
Li, Danxun .
JOURNAL OF HYDROLOGY AND HYDROMECHANICS, 2020, 68 (03) :242-248
[34]   Studies on gas concentration reconstruction methods for simultaneous temperature and H2O concentration tomographic imaging in a flame based on tunable diode laser absorption spectroscopy [J].
Zhai, Yunchu ;
Wang, Fei .
OPTICAL ENGINEERING, 2021, 60 (02)
[35]   Coherent structures over riblets in turbulent boundary layer studied by combining time-resolved particle image velocimetry(TRPIV),proper orthogonal decomposition(POD),and finite-time Lyapunov exponent(FTLE) [J].
李山 ;
姜楠 ;
杨绍琼 ;
黄永祥 ;
吴彦华 .
Chinese Physics B, 2018, (10) :399-408
[36]   Coherent structures over riblets in turbulent boundary layer studied by combining time-resolved particle image velocimetry (TRPIV), proper orthogonal decomposition (POD), and finite-time Lyapunov exponent (FTLE) [J].
Li, Shan ;
Jiang, Nan ;
Yang, Shaoqiong ;
Huang, Yongxiang ;
Wu, Yanhua .
CHINESE PHYSICS B, 2018, 27 (10)