文献类型：期刊文献

英文题名：A GPU-accelerated particle-detection algorithm for real-time volumetric particle-tracking velocimetry under non-uniform illumination

作者：Zhao, Yu[1];Ma, Xiaojun[2];Zhang, Chengbin[1];Chen, Jiujiu[2];Zhang, Yuanhui[1]

第一作者：Zhao, Yu

通讯作者：Zhang, YH[1]

机构：[1]Univ Illinois, Dept Agr & Biol Engn, Urbana, IL 61820 USA;[2]Beijing Union Univ, Coll Biochem Engn, Beijing, Peoples R China

第一机构：Univ Illinois, Dept Agr & Biol Engn, Urbana, IL 61820 USA

通讯机构：[1]corresponding author), Univ Illinois, Dept Agr & Biol Engn, Urbana, IL 61820 USA.

年份：2021

卷号：32

期号：10

外文期刊名：MEASUREMENT SCIENCE AND TECHNOLOGY

收录：;EI(收录号：20212810620350);Scopus(收录号：2-s2.0-85109447269);WOS:【SCI-EXPANDED(收录号:WOS:000664293900001)】；

基金：The authors acknowledge the support from BESS lab at University of Illinois through a Research Assistantship to the first author, and China National Key R&D Program (Grant No. 2018YFC0705204) to allow collaboration and visiting scholar exchange.

语种：英文

外文关键词：volumetric particle tracking velocimetry (VPTV); graphics processing unit (GPU); real-time; corner detection

摘要：Real-time volumetric particle tracking velocimetry (VPTV) equipped with field-programmable gate array (FPGA) cameras has been used for open-space, low particle density, and large-scale airflow measurements with long measurement periods. However, the particle detection accuracy of FPGA cameras is inevitably hindered by non-uniform illumination, resulting in a reduction in the particle detection ratio and positional accuracy. In this article, we propose to use both synchronized FPGA and grayscale cameras in a VPTV system, where grayscale cameras utilize a new algorithm based on two-frame centroid and corner extraction (TFCCE) under non-uniform white-light illumination. To keep the frame rate of the FPGA cameras the same, the TFCCE algorithm was accelerated by a graphics processing unit (GPU). The simulation results showed that the 2D particle detection ratio of TFCCE was enhanced to approximately 80% with a positional accuracy of 0.57 pixels, compared to 30% and 0.94 pixels for the single-frame centroid extraction used in the FPGA. The GPU version of TFCCE was 15.09 times faster than the CPU version, resulting in a calculation time of 4.55 ms per image, compared to 68.70 ms when using the CPU. This system was also validated by the measurement of a turbulent jet flow in real-time at 120 fps. The experimental results correspond well with data published in the literature. Therefore, this new algorithm can improve VPTV systems in terms of particle detection ratio and positional accuracy in real time under conditions of non-uniform illumination.