Classification of Microstructures of Al–Si Casting Alloy in Different Cooling Rates with Machine Learning Technique

Abstract

The classification of the microstructures of Al–Si–Mg casting alloy in different cooling rates was accomplished by using our originally developed methods and machine learning techniques. The mechanical properties of the samples were slightly increased with the increase of cooling rates. The microstructures of the samples were similar because of the approximate cooling rates. High classification rates of about 80% to 90% were obtained using the software with machine learning techniques developed by us. The classification rate change with the number of images in training data was tested and a suitable number of images for training in the machine learning process was found.

Fig. 4 The flow diagram of classification process.