Appl Opt. 2021 Aug 1;60(22):6538-6546. doi: 10.1364/AO.427571.
Herein, a calibration procedure to determine the depth positions of particles in a microfluidic channel via astigmatism particle tracking velocimetry (APTV) has been described. A neural network model focusing on the geometrical parameters of distorted particle images was developed to calibrate APTV. To demonstrate the efficiency of this procedure, the Poiseuille flow and depth of the particles, and dispersions in the microchannel were studied. The depth positions were determined with an uncertainty of ±1µ. The present results suggest that the particle position dispersion could be a result of the degree of particle image deformation and its deviation.
本文描述了一种通过像散粒子跟踪测速法（APTV）确定微流道中粒子深度位置的校准程序。开发了一个专注于变形粒子图像几何参数的神经网络模型来校准 APTV。为了验证该程序的效率，研究了微通道中的泊肃叶流、粒子深度以及分散度。深度位置的确定不确定度为±1µ。本研究结果表明，粒子位置的分散可能是粒子图像变形程度及其偏差的结果。
