100 kHz CH2O imaging realized by lower speed planar laser-induced fluorescence and deep learning

ZHANG，WEI1; DONG，XUE1; SUN，ZHIWEI2; ZHOU，BO3; WANG，ZHENKAN4; RICHTER，MATTIAS4

2021-09-13

10.1364/OE.433785

Optics Express   影响因子和分区

1094-4087

This paper reports an approach to interpolate planar laser-induced fluorescence (PLIF) images of CH2O between consecutive experimental data by means of computational imaging realized with convolutional neural network (CNN). Such a deep learning based method can achieve higher temporal resolution for 2D visualization of intermediate species in combustion based on high-speed experimental images. The capability of the model was tested for generating 100 kHz PLIF images by interpolating single and multiple PLIF frames into the sequences of experimental images of lower frequencies (50, 33, 25 and 20 kHz). Results show that the prediction indices, including intersection over union (IoU), peak signal to noise ratio (PSNR), structural similarity index (SSIM), and time averaged correlation coefficient at various axial positions could achieve acceptable accuracy. This work sheds light on the utilization of CNN-based models to achieve optical flow computation and image sequence interpolation, also providing an efficient off-line model as an alternative pathway to overcome the experimental challenges of the state-of-the-art ultra-high speed PLIF techniques, e.g., to further increase repetition rate and save data transfer time.

SCI ; EI

英语

其他

WOS:000695619200105

20213710897506

Convolutional neural networks ; Data transfer ; Fluorescence ; Interpolation ; Laser optics ; Laser produced plasmas ; Optical flows ; Signal to noise ratio

Information Theory and Signal Processing:716.1 ; Light/Optics:741.1 ; Laser Applications:744.9 ; Numerical Methods:921.6

PHYSICS

2-s2.0-85114823066

Scopus

1.China-UK Low Carbon College,Shanghai Jiao Tong University,Shanghai,200240,China
2.Centre for Energy Technology (CET),School of Mechanical Engineering,The University of Adelaide,Adelaide,5005,Australia
3.Department of Mechanics and Aerospace Engineering,Southern University of Science and Technology,Shenzhen,China
4.Division of Combustion Physics,Lund University,Lund,P. O. Box 118,SE-221 00,Sweden

ZHANG，WEI,DONG，XUE,SUN，ZHIWEI,et al. 100 kHz CH2O imaging realized by lower speed planar laser-induced fluorescence and deep learning[J]. Optics Express,2021,29(19):30857-30877.

ZHANG，WEI,DONG，XUE,SUN，ZHIWEI,ZHOU，BO,WANG，ZHENKAN,&RICHTER，MATTIAS.(2021).100 kHz CH2O imaging realized by lower speed planar laser-induced fluorescence and deep learning.Optics Express,29(19),30857-30877.

ZHANG，WEI,et al."100 kHz CH2O imaging realized by lower speed planar laser-induced fluorescence and deep learning".Optics Express 29.19(2021):30857-30877.