Optimization of Alloying of HEAT Resistant CORE Wires for ARC Spraying By Neural Network Modeling

A core wire of Fe-25Cr-5Al-Si-Ti type was developed using neural network modeling of particle oxidation at arc spraying. A relationship between particle oxidation and coating heat resistance was grounded. A criterion of minimal oxygen input into alloying elements during spraying was chosen as a criterion for optimization of quantity of such additives as Si, Ti ets. Modeling results were verified by thermogravimetry at 700°C and structure analysis by means of scanning electron microscopy. It revealed reasons of additive’s influence for high temperature heat resistance of such coatings. Developed core wire was used to produce heat resistant coating by active arc spraying.

Key words: neural network modeling, oxidation degree, arc spraying, core wire, alloying system.