Vibration separation of bulk construction mixtures by measurement sizes on sieve classifiers

Abstract The vibrational separation of bulk building mixes by size is studied using stochastic-based sieve classifiers. The system of stochastic differential equations is constructed to determine the linear density of particles on the surface of the classifier sieves. The linear density of particles on sieves is approximated by white noise, which allows the system of equations to be called stochastic. The solution of the system of stochastic differential equations with respect to the average value of a random process is determined. We construct an approximate solution for the distribution density and transition probabilities of a random process using the properties of the white noise. Knowing the density of the distribution of the number of particles on the surface of the classifier sieves determines all its characteristics of interest. The obtained solutions allow us to calculate the extraction coefficient and evaluate the efficiency of separation.