Authors : Batyrbek Suleimenov, Laura Sugurova, Aituar Suleimenov and Alibek Suleimenov
Abstract: This study had solved the problem of reliability of production equipment with intelligent technical condition diagnostics system. The purpose of the study is to provide an adaptive model of operational system diagnostics and predicting of possible emergencies for electrothermal furnace based on the comprehensive change of its diagnostic parameters. To achieve this purpose, we used methods of artificial neural networks, fuzzy logic, expert evaluation and mathematical modeling. Based on the expert method and matrix planning of fractional factorial experiment, we formed the base of fuzzy production rules for setting up and training of adaptive diagnostic models of electric furnaces. It was found that ANFIS Model has the lowest value of the relative electric furnace state error recognition. The practical implementation of the proposed model is realized in the development of a production equipment diagnostics subsystem of the sintering floor at Novodzhambul sky phosphate plant.
Batyrbek Suleimenov, Laura Sugurova, Aituar Suleimenov and Alibek Suleimenov, 2017. Neuro Fuzzy Model For Equipment Health Management in Yellow Phosphorus Production Process. Journal of Engineering and Applied Sciences, 12: 7889-7896.