Authors : Batyrbek Suleimenov, Laura Sugurova, Aituar Suleimenov and Alibek Suleimenov
Abstract: The aim of this research is the development and testing of intelligent system for equipment health management in the technological process of yellow phosphorus production. In the course of research, the methods of mathematical modeling, experimental design methods, methods of fuzzy modeling, methods for creating and training neural networks and neural network algorithms were used. The peculiarities of the technological process of phosphorus electric smelting are discussed. The three-step procedure of developing intelligent or hybrid models for the management process is proposed to increase the effectiveness of this process on the example of ore-thermal smelting of phosphate ore. A subsystem for calculating the power on the mean level of the automated management system of technological process parameters with the calculations readability once in 10 min is developed which allows stabilizing the temperature under the furnace roof arch which in turn leads to the reduction of phosphorus loss with the exhaust gases out of the condenser. It is indicated that the mean level subsystem determines the optimal values of power depending on the voltage level, linear current, the arrangement of the electrodes on the crossbar and the average temperature under the furnace roof arch.
Batyrbek Suleimenov, Laura Sugurova, Aituar Suleimenov and Alibek Suleimenov, 2018. Intelligent Systems for Equipment Health Management and Optimum Control in Phosphate Production. Journal of Engineering and Applied Sciences, 13: 607-618.