The article discusses the relationship between the mass of the laboratory sample and the homogeneity of its particle size distribution. The aim of the work is to estimate the limits of the sample mass reduction, at which it remains representative in particle size distribution. A relation was pointed out between the chemical and physical properties and the particle size distribution of fertilizers. The use of this parameter as one of the basic physical properties of industrially produced mineral fertilizers was justified. At the same time, using a smaller sample will reduce the time for analysis in industrial laboratories. An experiment was proposed and implemented to assess the representativeness of sample of fertilizers with different masses. Samples of several brands of industrially produced granulated mineral fertilizers were studied. A sieve analysis of samples was carried out in accordance with accepted standards (for < 1 mm, 1-2 mm, 2-3.15 mm, 3.15-4 mm, 4-5 mm, 5-6.3 mm, > 6.3 mm fractions). A comparison between the obtained results and industry-specific technique for determining the particle size distribution on the woven sieve was given. According to the obtained data, the main statistical characteristics of the analysis were calculated: mathematical expectation (average value), standard deviation and confidence interval. The homogeneity of the average values and variances of the obtained samples for the 50 and 150 g of fertilizers was investigated using Student's and Fisher's tests for a 0.05% level of significance. To confirm the test results, a graphic distribution of sample with different mass and the fraction < 2 mm was built. Conclusion about the allowable mass of a representative sample of granular mineral fertilizers for analyzing the particle size distribution and the associated with physical and chemical properties of fertilizers was made.
The paper shows and investigates the technique of classifying the particle size of powder and granulated materials. The objects of the study are industrially produced mineral fertilizers. Samples with different composition (about five types of mineral fertilizers) and various degrees of particle size (less than 100 µm, less than 500 µm and granules of 2-5 mm) were examined. The samples particles have an irregular shape, close to spherical (in the case of granules) or cubic (in the case of powders). To improve the accuracy and eliminate the particle shape influence on analysis, the preliminary pressing of samples on a boric acid substrate was used. The keynote of the proposed technique is to obtain an optoelectronic image of an object with a resolution of at least 640x480 pixels (a three-dimensional matrix of pixel intensity in the Red-Green-Blue (RGB) system). Next, the area of analysis is separated from the obtained image and transformed into grayscale (a two-dimensional matrix of pixel intensities with a resolution of at least 200x200 pixels). The influence of external illumination (gradient, temperature and brightness) is eliminated by the grayscale image differentiation. The result is the “surface map” of the sample, which reflects defects in the pressed structure (patterns, which are responsible for the size of the particles). According to the found patterns, the samples are classified according to their particle size. Four classification algorithms were investigated (linear, linear with L1 and L2 regularization, and a nonlinear “random forest”). All proposed approaches are automated and implemented in the Python 3.6 programming language. There is provided the selection of the operating parameters of all the described algorithms.
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