Goncharov S. Simulation and optimization of separation processes of mineral processing on basis of the dynamic effects of high-energy ultrasound.

In dissertation optimization model of identification of mineralogical and technological types of ore to improve the efficiency of separation processes for the preparation of ore for processing based on the dynamic effects of high-energy ultrasound in the ore pulp was developed. Iterative method of fuzzy identification of mineral species in ore, which allows a confidence level of 0.98 was improved. It is shown that on the basis of fuzzy inference Sugeno and subtractive clustering performance closed loop milling slurry density and its solid phase in a closed loop classifier drain grinding can be made of mineral types identification. First proposed in the process of subtractive clustering features classified ore correction vector defining the dimensions of the rules for each coordinate, implement based on the evaluation of the variance of the amplitude of high-frequency ultrasonic vibrations, past a fixed distance in the test pulp. First established that the space for the detection of informative processed ore mineral types can be generated by evaluating the changes in the function of particle size on the ground ore pulp stream at a certain point of the process under influence of ultrasound radiation pressure of high specific intensity.