Artificial Intelligent Aided Analysis and Prediction of High-Velocity Oxyfuel (HVOF) Sprayed Cr₃C₂-25NiCr Coatings

In this work, an artificial neural network (ANN) model was developed to investigate the application of Cr₃C₂-25NiCr coatings by HVOF spraying and predict the resulting properties based on flow rates, stand-off distance, and other parameters. HVOF coatings were sprayed and tests were conducted to generate data for training, validating, and testing the model. The model was trained with an R-value of 0.99965 to predict the relationship between spray parameters and coating properties including hardness, porosity, and wear rate. The reliability and accuracy of the model was subsequently verified using independent test sets.