This paper used BP(Neural Networks) to establish parameter optimization design method for Zr-4 clad tube belt grinding. The BP can get strong nonlinear mapping capability through training, obtain better grinding parameter model; GA(Genetic Algorithm) is not dependent on the specific situation of the problem and it has strong robustness, so it can provides optimization framework for Zr-4 clad tube belt grinding parameter optimization design of nonlinear optimization. This paper optimized the single objective and multi-objective of the abrasive belt life n and grinding roughness R_z, obtained satisfied optimization results and the corresponding grinding conditions.
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