Recognition of NiCrAlY coating based on convolutional neural network

This paper established an eight-layer convolu-tional neural network to automatically recognize the characteristic phases of the NiCrAlY coating, the coating/substrate interface, and the oxide layer. Using this neural network, the Cr-rich phase, the coating/substrate interface, and the oxide layer, as the features of the NiCrAlY coating, were successfully identified and retrieved at different constant oxidation temperatures. Based on this achievement, the variations of the Cr-rich phase distribution and the changes of the oxide layer thickness calculated by the network were obtained, which are all consistent with the trend of the oxidation kinetic curves at different temperatures; the preliminary intelligent calculation of oxidation kinetics of the coating was carried out through the thickness of the oxide layer from the SEM images.