基于遗传算法的铣削加工参数模糊优化系统研究

优化铣削参数对于降低铣削加工成本、提高生产率有重要的作用。传统的铣削参数优化模型中，铣削参数和条件约束的匹配取值往往是通过实际加工的经验获得，这种结果具有不确定性和模糊性。文章分析了模糊参数优化的数学模型，根据模糊集合原理将模糊模型转化为一个传统的单目标模糊优化问题，借用IDEF1x方法建立了铣削参数模糊数据库模型，并运用遗传算法（GA）为优化引擎开发实现了模糊优化系统。给出的运行实例表明该优化系统对铣削参数优化具有更好的效果，同时，系统为CAPP优选铣削参数提供了支持平台。

Reseach on Fuzzy Optimization System of Milling Parameter Based on Genetic Algorithm

The optimization of cutting parameters is the key to reduction of manufacturing cost and promotion of productivity. Compared to the uncertainty and fuzziness of the traditional milling condition optimization model, within which the values of milling parameters and constraints are commonly obtained by practical experiences, a fuzzy cutting parameter optimization model is analyzed and converted to an identical single- objective crisp- optimization problem. The IDEF 1 x method is used to build the fuzzy milling parameters supporting database model. And the GA approach is introduced to establish the optimization engine to provide the solution to this problem. A software system, which provides a platform for CAPP in milling parameter optimization selection, is setup and an operational case shows the superiority of this fuzzy optimization modus.