Determination of Particle Size Distribution by Par-Tec® 100: Modeling and Experimental Results (original) (raw)
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Comparison of Particle Size Distributions Measured Using Different Techniques
Particulate Science and Technology, 2005
In this article, particle size distributions (PSDs) measured by different techniques, including image analysis (IA), laser diffraction (LD), ultrasonic attenuation spectroscopy (UAS), and focused-beam reflectance measurement (FBRM), are compared for spherical glass beads and nonspherical silica flakes. It is shown that particle shape strongly affects the results obtained by different techniques. For spheres, the PSDs obtained by IA, LD, and UAS agree well. There is no consistent result among different particle measurement techniques for nonspherical particles. The conversion between PSDs obtained by IA, LD, and UAS has been based on particle shape factors. Caution must be exercised when a measured chord length distribution (CLD) is used to indicate the PSD during a process because the CLD result obtained by FBRM is complex, depending not only on the PSD, but also on particle optical properties and shape. Keywords Particle size distribution (PSD), image analysis (IA), laser diffraction (LD), ultrasonic attenuation spectroscopy (UAS), focused-beam reflectance measurement (FBRM), chord length distribution (CLD)
Obtaining Particle Size Distribution from Chord Length Measurements
Particle & Particle Systems Characterization, 2006
The Lasentec focused-beam reflectance measurement (FBRM) is becoming a more popular technique to measure particle size on-line in different applications. The FBRM uses a focused beam of laser light that scans across particles passing in front of the probe window to measure a chord length distribution (CLD). Compared with CLD information, the particle size distribution (PSD) is more useful because it is directly related to product quality and process productivity. However, it is not straightforward to convert a measured CLD into its corresponding PSD accurately due to the lack of a theoretical analysis for non-spherical particle systems. In this paper, firstly a general model to translate a PSD into its corresponding CLD is given for different shapes including spherical, ellipsoidal and more general non-spherical particles. Then an iterative inversion method is developed to obtain the PSD from a measured CLD. Finally, effectiveness of the proposed PSD-CLD model and iterative inversion method has been extensively validated by experiments.
Challenges in particle size distribution measurement past, present and for the 21st century
Progress in Organic Coatings, 1997
The field of particle size distribution (PSD) characterization and measurement has experienced a renaissance over the past ten years. This revitalization has been driven by advances in electronics, computer technology and sensor technology in conjunction with the market pull for PSD methods embodied in cost effective user friendly instrumentation. The renaissance can be characterized by at least four activities.
Chemical Engineering Science, 2015
Information about size and shape of particles produced in various manufacturing processes is very important for process and product development because design of downstream processes as well as final product properties strongly depend on these geometrical particle attributes. However, recovery of particle size and shape information in situ during crystallisation processes has been a major challenge. The focused beam reflectance measurement (FBRM) provides the chord length distribution (CLD) of a population of particles in a suspension flowing close to the sensor window. Recovery of size and shape information from the CLD requires a model relating particle size and shape to its CLD as well as solving the corresponding inverse problem. This paper presents a comprehensive algorithm which produces estimates of particle size distribution and particle aspect ratio from measured CLD
A simple and fast matlab-based particle size distribution analysis tool
International Journal of Computational Methods and Experimental Measurements, 2021
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.
Powder technology, 2002
The measurement of particle size distributions (PSD) of model anisotropic particles with regular cylindrical or platelet morphologies has been previously studied with several different instruments, and good correlations with image analysis were found for certain specific measurement methods. The correlation was found to be dependent on particle morphology. For cylindrical glass fibres, photocentrifuge data gave good correlations with image analysis, whereas for platelets the laser diffraction method gave the best correlation with image analysis. The study has been enlarged to investigate less regular-shaped particles found in real practical systems, namely, flake-like particles of mica and rod-like copper oxalate precipitates. The correlation between laser diffraction data and image analysis for the flake-like mica is very good and confirms the approach used with model platelets. The copper oxalate rod-like precipitates also confirm the applicability of the photocentrifuge particle size distribution measurement for such particle shapes. In both cases, there are, however, limitations on the interpretation of the particle size instrument data. Some shape information from microscopic images is needed to make some assumptions to simplify the deconvolution of size and shape from the data collected. D
Estimation of particle size distribution from cross-sectional particle diameter on the cutting plane
Advanced Powder Technology, 2010
A particle size distribution (PSD) estimation method based on light-scattering properties was validated on experimental visible/near-infrared scattering spectra of polystyrene suspensions, with a nominal particle size ranging from 0.1 to 12 μm in diameter. On the basis of μ s and g spectra extracted from double integrating sphere measurements, good PSD estimates were obtained for particles ≥1 μm. The particle volume fraction estimates in the case of μ s were close to the target concentrations, although influenced by small baseline fluctuations on the spectra. For submicrometer particles, on the other hand, the non-oscillating μ s spectra lack discriminating power, resulting in erroneous PSD estimates. The reduced scattering coefficient spectra (μ s ′) were found less useful for particle size estimation as they lack a characteristic shape, causing an over-or underestimation of the distribution width. In summary, the estimation routine proved to deliver PSD estimates in line with the reference measurements for micrometer-sized or larger particles based on their μ s and g scattering spectra. Additional validation on more polydisperse samples forms the next step before going to bimodal PSD estimates.
Quantification of particle size and concentration using in-line techniques and multivariate analysis
Powder Technology, 2020
We study means of extracting quantitative information about particle attributes using state-ofart in-line and off-line particle measurements and analysis techniques. The approach comprises a combination of image analysis, laser diffraction, inversion of chord length distribution, and multivariate analysis. Polystyrene particle suspensions are used as the model system to provide a wide range of particle loadings (up to 10 wt%), sizes (<90 to 800 µm) and shapes. We identify key challenges and limitation of the in-line imaging and chord length measurements; particularly, an upper limit of particle number density of 10,000 g-1 is observed, as well as the impact of internal reflections from large and transparent particles. The latter phenomena deteriorate the accuracy of the chord length distribution and the subsequent particle size estimation using inversion algorithms. The study demonstrates the use of multivariate analysis 2 for quantifying particle size and concentration, which yields relative errors of 6 and 11 %, respectively.
Comparison of particle-size analyzing laboratory methods
Environmental engineering and management journal
Particle size distribution is one of the most influential factors of most soil physical and even some soil chemical characteristics. As modern measurement techniques are being introduced, the need for comparing new methods with older methodologies arises because comparability means data continuity. Here, three institutes conducted a comparison of particle size measurement among the laser, areometer and pipette techniques. The purpose of the comparison was to a) discover any differences among operators, laboratories, and techniques; b) identify if there were any differences and if they could be linked to soil type (e.g. high clay, loam, or sand content) or particle size range; and c) understand if the laser diffraction method gave results that were significantly larger than the other methods of any size fraction. There was no statistically proven difference between the two operators examined based on the pipette method's result. The comparison of two of the institutes' pipett...