3D particle streak velocimetry by defocused imaging--颗粒学报PARTICUOLOGY

Dong, X., Wang, X., Zhou, W., Wang, F., Tang, X., & Cai, X. (2023). 3D particle streak velocimetry by defocused imaging. Particuology, 72, 1-9. https://doi.org/10.1016/j.partic.2022.02.002

3D particle streak velocimetry by defocused imaging

Xiangrui Dong^{a b}, Xiaoxiao Wang^{a b}, Wu Zhou^{a b *}, Fangting Wang^{a b}, Xinran Tang^{a b}, Xiaoshu Cai^{a b}

a School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
b Shanghai Key Laboratory of Multiphase Flow and Heat Transfer for Power Engineering, Shanghai 200093, China

10.1016/j.partic.2022.02.002

Volume 72, January 2023, Pages 1-9

Received 15 August 2021, Revised 8 February 2022, Accepted 15 February 2022, Available online 25 February 2022, Version of Record 3 March 2022.

E-mail: zhouwu@usst.edu.cn

Highlights

• Defocusing particle streak velocimetry (DPSV) is proposed for 3D flow field measurement.

• Curvilinear integral of Gaussian distribution is used to fit curved trajectories.

• Image processing mainly includes image segmentation and parameter recognition.

• DPSV can measure 3D velocity field in jet and microchannel flow by monocular system.

Abstract

Particle streak velocimetry (PSV) has become one of the important branches of flow filed measurements. It extracts velocity information from particle trajectories captured by single frame long exposure images. Since the defocus of moving particle is inevitable during a long exposure time and under a large magnification, a novel three-dimensional (3D) velocity measurement method named defocusing particle streak velocimetry (DPSV) is proposed in this paper. On the one hand, an extension from two-dimensional (2D) to 3D velocity measurement with a monocular system is carried out. The depth information of the particle, which reflects the position in the third dimension, is indicated by the defocusing degree (characteristic parameter σ) of the particle images. The variation of σ along the trajectory is recognized by surface fitting of the gray value distribution of particle images, assuming that σ varies linearly along the trajectory. On the other hand, based on the linear fitting for the straight trajectory, an arc fitting model is developed for curved trajectories which are commonly captured in turbulent flow. The relationship between σ and the particle depth position z is experimentally calibrated using a LED light and a diaphragm. Finally, the DPSV method is verified in a submerged jet flow field as well as in a microchannel flow field to obtain the 3D velocity field with single monocular system.

Graphical abstract

Keywords

Defocusing particle streak velocimetry; Curve trajectory; Three-dimensional velocity; Gray value distribution

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