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.
imaging methods, particle analysis, particle sizing
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