Parameter Recognition and Optimization of Residual Stress Prediction Model Based on Genetic Algorithm

Building a forecast model of cutting surface's residual stress due to different cutting parameters and finding the optimal combination of cutting parameters is the demand of developing ultra precision industries such as aviation and aerospace. Owing to the limitation of the least square method and other conventional methods, genetic algorithm was introduced into the parameter identification of cutting surface's residual stress forecast model and to optimize cutting parameters. In this way, a cutting surface's residual stress forecast model of aluminum alloy is given. By contrast, genetic algorithm is more suitable to identify parameters of cutting surface's residual stress forecast model, and to guarantee the optimal cutting parameter combination.