Известия Томского политехнического университета: Инжиниринг георесурсов (May 2019)
Computer model for stochastic control of the ore flotation process considering grinding equipment reliability
Abstract
The urgency of the discussed issue is caused by the necessity to improve the adequacy of the model for the ore flotation process control. The main aim of the study: to develop a generalized computer model for stochastic control of the ore flotation process considering the impact of reliability parameters of grinding equipment and features of the original ore. The methods used in the study: methods of applied statistics (method of the expert evaluations, methods for identification of the probability distribution function, methods of regression analysis), methods of simulation modeling. The results: The statement of optimal control problem of ore flotation process is substantiated as a problem of stochastic programming. The generalized computer model is developed for stochastic control of the ore flotation process. Based on this model the authors have developed a computer model for the stochastic control of copper-molybdenum ore flotation process which takes into account the impact of reliability parameters of grinding equipment and the characteristics of the initial ore on flotation efficiency. The developed model includes the probabilistic simulation model of failure occurrences and recovery of the grinding equipment, the stratified model of functioning of ore grinding technological system and the model of formation of efficiency parameter of flotation process. As a result of carried out simulation experiments with the developed computer model the optimal values of reagents consumptions and technological parameters of ore flotation are defined. The use of simulation model of ore grinding technological system in the computer model, taking into account the reliability of the grinding equipment, allows increasing essentially the adequacy of the computer model as a whole, providing a possibility of obtaining more accurate solutions to the problem of the stochastic optimal control of flotation process.
