Research On The Relationship Between Fractal Dimension And Classification Resistance Of Carriers For Premix

Premix is a kind of semi-manufactured feed, that one or more kinds of microcomponents (microelements, vitamins, Synthesis of amino acids, drug additives) disperse in carriers or thinners evenly with appropriate proportion, uniformity degree is an important index for its quality. In transport or storing process and so on, formed homogeneous state will be destroyed inevitablly, the quality must be reduced by this classification. The choose of carriers or thinners, as well as the method of transport and the height of barn, extently effects classification, the more powerful of the carriers’(or thinners’) performance of classification resistance, the better. To a great extent, carriers’(or thinners’) performance of classification resistance rest on its microcosmic surface, adsorptivity, flowability, particle size distribution and so on. For a long time, microcosmic surface is too complex to quantitative analysis, fractal geometry theory makes the quantitative analysis possible, and supplies a method for correlation study between carriers’(or thinners’) microcosmic surface and performance of classification resistance.In this paper, based on former positive results came from the powders research using fractal geometry theory, taking the feed grade FeSO4·H2O as carrying object, eight frequently-used carriers of premix had been selected and the correlation analysis of their fractal dimension, angle of repose, volume weight, performance of classification resistance had been carried through. The performance of classification resistance representation model about fractal dimension and angle of repose also had been established in this essay.In this paper, following prats were studied:The equation of linear regression obtained from calculations of carriers’ fractal dimension with the perimeter-area fractal dimension and differential box-counting fractal dimension methods based on the SEM images was highly significant(r>Rmin).The result showed that using the two methods to calculate the fractal dimension of carrier is feasible. The value of boundary fractal dimension calculated by perimeter-area method ranged from1to2, while the value of surface fractal dimension calculated by differential box-counting method ranged from2to3. Carriers’ Fractal dimension calculated by this two methods don’t have corresponding relationship.The effect of fractal dimension on angle of repose and volume weight was investigated. Perimeter-area fractal dimension of8selected carriers didn’t have significant relationship with angle of repose and volume weight (p>0.05); the relationship between differential box-counting fractal dimension and angle of repose was not significant (p>0.05), however, the relationgship with volume weight was significant(p<0.05), regression equation was as follows:γ=-3311D2+8123. The results showed that, comparatively speaking, the microcosmic surface exerted a considerable influence on volume weight, volume weight got smaller with the imcrease of differential box-counting fractal dimension.The effect of fractal dimension, angle of repose and volume weight on performance of classification resistance was investigated. The effect on performance of classification resistance by volume weight was not significant (p>0.05); the effect on performance of classification resistance by angle of repose was significant(p<0.05), the model between performance of classification resistance and angle of repose was linear, as follows: α=0.01260y-0.0933; the effect on performance of classification resistance by fractal dimension was more complex. To eight carriers, the relationship was not significant(p>0.05); To four organic carriers(corn powder, rice bran, whole wheat flour, bean pulp), the effect on performance of classification resistance by perimeter-area fractal dimension and differential box-counting fractal dimension was significant (p<0.05). Regression equation as follows:α=3.3706D1-3.3550(Sig.F<0.05)、α=3.3032D2-7.2139(Sig.F<0.05); Synthesizing the fractal dimensiong and angle of repose’s effect on performance of classification resistance, a polynomial regression equation was set up. Through the equation, interaction of perimeter-area fractal dimension and differential box-counting fractal dimension is the greatest impact on performance of classification resistance.