Estimation of measurement error and depth of field in PDIA experiments: a comparative study using water droplets and a calibration target

Abstract

The particle/droplet image analysis (PDIA) technique is often used for droplet sizing in sprays. Successful use of PDIA for drop size measurement in sprays mandates careful calibration, and determination of the depth of field (DOF) for particles of different size classes. This is typically done with a calibration target that has circles etched on it. In the present study, a calibration experiment was performed with a calibration target as well as droplets, to evaluate the uncertainties in the measured sizes and also to compare the measured DOF values. A continuous-jet droplet generator was used to produce mono-disperse droplets of sizes ranging from 54–393 µm, and the calibration glass plate used contained circles of sizes ranging from 20–400 µm. Images of these were captured using a CCD camera equipped with a long-distance microscope, and were processed using a code written in MATLAB®. Differences in the measured sizes of droplets and circles, and their DOF values are reported. It was observed that the use of the calibration target led to an underestimation of the error in droplet size measurements, and an overestimation of the DOF. For the droplets, the measurement error was observed to be less than 5%, with the parameters chosen.

Particle mass flow determination in dust-laden supersonic flows by means of simultaneous application of optical measurement techniques

“…This is valid as long as shadows of particles in supersonic flows behave similar to circular dots on a glass-target. A comparison between bubble-based and glass targetbased calibrations was made in (Senthilkumar et al 2020), showing differences in the detected measurement volume thickness. In future studies, it has to be checked whether shadowgraphy's measurement volume thickness, measured by means of a glass target without flow, can be applied to the supersonic flow environment.…”

“…Assuming that the latter one is correct and considering the fact that shadowgraphy measured the particle size distribution and velocity properly, the main driver for the increased G p could be an underestimated measurement volume thickness d shadow . However, in the study of (Senthilkumar et al 2020), it is proposed that a DOF calibration with the help of a glasstarget tends to an overestimated d shadow .…”

“…Direct imaging of particles is a straightforward technique for determining velocity and size even from irregular-shaped particles. Multiple names were used for this technique in the past: shadowgraphy technique (Castanet et al 2013, Dehnadfar et al 2012, Legrand, Nogueira, Lecuona and Hernando 2016, Wang et al 2017, particle droplet image analysis (PDIA) (Anand et al 2012;Castanet et al 2013;Ju et al 2012;Kashdan et al 2003;Senthilkumar et al 2020), backlight photography (Zhou et al 2020), image processing technique (Koh et al 2001;Lee and Kim 2004), imagebased drop-sizing techniques (Fdida and Blaisot 2009), shadow imaging (Putkiranta et al 2008), or just imaging (Kim and Kim 1994). In the following, the term shadowgraphy is used.…”

“…As discussed in (Kapulla et al 2008), several detection settings of the DaVis software can have a significant effect on the detected particle size and, hence, on the particle mass flow rate. As mentioned in (Legrand et al 2016;Senthilkumar et al 2020), a check of how many particles are detected within the shadowgraphy measurement volume is recommended. These two aspects -influence of particle detection settings on G p and the particle detection rate, are missing in the uncertainty analysis made in (Allofs et al 2022).…”