TY  - JOUR
T1  - Intelligent Systems for Equipment Health Management and
Optimum Control in Phosphate Production
AU - Suleimenov, Batyrbek AU - Sugurova, Laura AU - Suleimenov, Aituar AU - Suleimenov, Alibek 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 3
SP  - 607
EP  - 618
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.607.618
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.607.618
KW  - Intelligent management systems
KW  -phosphorus electric smelting
KW  -equipment health management
KW  -fuzzy models
KW  -neural networks models
KW  -linear current
AB  - 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.
ER  -