Design Of The Artificial Neural Network Expert System And The Application In Fe Base Corrosion-Resistant Alloy

The composition and processing technology of new materials is often determined by a lot of experiments because the relation among the chemical composition, processing and properties of materials is not very clear. Computer modeling greatly shortens the development period of the new materials, new processes and new designs.An expert system based on artificial neural network is built. The prediction program and the optimization program of the artificial neural network expert system are designed. The Back Propagation neural network learning programming is improved. The artificial neural network expert system man-machine interface is designed. This system software can be used to the pretreatment of data, the expansion and revision of sample, the prediction and the optimization of properties of ferrous alloy.Effects of Si, C, Mn on the corrosion rate and bending strength of Fe based corrosion-resistance alloy are predicted with the system. The composition of Fe based corrosion-resistance alloy is optimized by the use of the system. Experiments show that the experimental data is closed to results predicted by the expert system. The artificial neural network expert system has a good compatibility in alloy design and performance prediction.