Prediction and Analysis of the Grit Blasting Process on the Corrosion Resistance of Thermal Spray Coatings Using a Hybrid Artificial Neural Network

Grit blasting as a pretreatment process for the substrate surface before thermal spraying is of great importance assuring service performance coatings. In this work, novel hybrid artificial neural network (ANN) was presented to optimize grit improve structural properties and corrosion resistance Different parameters were combined pretreat surface, corresponding roughness, interface adhesion strength obtained. Hence, backpropagation (BP) model optimized by genetic algorithm (GA) address poor regression roughness accuracy traditional fitting models; processing utilized inputs GA–BP model; used outputs. The correlation coefficient R reached exceeded 0.90, three error values less than 1.75 on prediction random samples. All these indicators demonstrated convincingly that obtained models possessed good performance, innovative time-saving optimization approach could be potentially employed comprehensive