Javascript is required
Search

Acadlore takes over the publication of IJCMEM from 2025 Vol. 13, No. 3. The preceding volumes were published under a CC BY 4.0 license by the previous owner, and displayed here as agreed between Acadlore and the previous owner. ✯ : This issue/volume is not published by Acadlore.

Open Access
Research article

A Simple and Fast Matlab-Based Particle Size Distribution Analysis Tool

jesus d. ortega1,
irma r. vazquez1,
peter vorobieff1,
clifford k. ho2
1
University of New Mexico, Albuquerque, NM, USA
2
Concentrating Solar Technologies, Sandia National Laboratories, Albuquerque, NM, USA
International Journal of Computational Methods and Experimental Measurements
|
Volume 9, Issue 4, 2021
|
Pages 352-364
Received: N/A,
Revised: N/A,
Accepted: N/A,
Available online: N/A
View Full Article|Download PDF

Abstract:

Particle size distribution is one of the most important physical properties of a particulate sample. Traditional particle-sizing methods to estimate a geometrical particle size distribution employ a sieve analysis (or gradation test), which entails filtering the particles through a series of sieves and measuring the weight remaining on each sieve to estimate the number-weighted particle size distribution. However, these two quantities have the same value only if particles are perfectly spherical and round. On the other hand, a particle sizer such as the Malvern particle size analyzer, which uses laser diagnostics to measure the particle sizes, can be a hefty investment. Alternatively, imaging techniques can be applied to estimate the size of these particles by scaling a reference dimension to the pixel size, which in turn is used to estimate the size of the visible particles. The focus of this work is to present a simple methodology using a DSLR camera and an illuminated LED panel to generate enough contrast. Using the camera and lens properties, the scale, or size, of any image can be obtained based on the mounting distance of the camera with respect to the target. An analysis tool was developed in MATLAB where the images are processed automatically based on the prescribed camera and lens properties embedded within the same image file and requiring the user to only input the mounting distance of the camera. So far, results show a positive agreement when comparing to measurements using ImageJ imaging tools and a sieve analysis. Future tests will analyze different particle sizes and types, as well as using a Malvern particle size analyzer to corroborate the results.

Keywords: Imaging methods, Particle analysis, Particle sizing

1. Introduction

2. Imaging Method

2.1 Pre-Analysis Requirements
2.2 Script Methodology
2.2.1 Particle cluster segmentation

3. Experimental Methodology

3.1 Camera Experimental Setup
3.2 Particle Sieve Analysis
3.2.1 Median particle diameter
3.2.2 Mean particle diameter
3.3 Imaging Method

4. Experimental Results and Discussions

4.1 Sieve Analysis
4.2 Imaging Method
4.2.1 Method constraints

5. Conclusions and Future Work

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare that they have no conflicts of interest.


Cite this:
APA Style
IEEE Style
BibTex Style
MLA Style
Chicago Style
GB-T-7714-2015
Ortega, J. D., Vazquez, I. R., Vorobieff, P., & Ho, C. K. (2021). A Simple and Fast Matlab-Based Particle Size Distribution Analysis Tool. Int. J. Comput. Methods Exp. Meas., 9(4), 352-364. https://doi.org/10.2495/CMEM-V9-N4-352-364
J. D. Ortega, I. R. Vazquez, P. Vorobieff, and C. K. Ho, "A Simple and Fast Matlab-Based Particle Size Distribution Analysis Tool," Int. J. Comput. Methods Exp. Meas., vol. 9, no. 4, pp. 352-364, 2021. https://doi.org/10.2495/CMEM-V9-N4-352-364
@research-article{Ortega2021ASA,
title={A Simple and Fast Matlab-Based Particle Size Distribution Analysis Tool},
author={Jesus D. Ortega and Irma R. Vazquez and Peter Vorobieff and Clifford K. Ho},
journal={International Journal of Computational Methods and Experimental Measurements},
year={2021},
page={352-364},
doi={https://doi.org/10.2495/CMEM-V9-N4-352-364}
}
Jesus D. Ortega, et al. "A Simple and Fast Matlab-Based Particle Size Distribution Analysis Tool." International Journal of Computational Methods and Experimental Measurements, v 9, pp 352-364. doi: https://doi.org/10.2495/CMEM-V9-N4-352-364
Jesus D. Ortega, Irma R. Vazquez, Peter Vorobieff and Clifford K. Ho. "A Simple and Fast Matlab-Based Particle Size Distribution Analysis Tool." International Journal of Computational Methods and Experimental Measurements, 9, (2021): 352-364. doi: https://doi.org/10.2495/CMEM-V9-N4-352-364
ORTEGA J D, VAZQUEZ I R, VOROBIEFF P, et al. A Simple and Fast Matlab-Based Particle Size Distribution Analysis Tool[J]. International Journal of Computational Methods and Experimental Measurements, 2021, 9(4): 352-364. https://doi.org/10.2495/CMEM-V9-N4-352-364