基于SVR和NSGA-II的钛合金铣削参数多目标优化 |
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引用本文: | 向国齐.基于SVR和NSGA-II的钛合金铣削参数多目标优化[J].航空精密制造技术,2016(5):36-40. |
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作者姓名: | 向国齐 |
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作者单位: | 攀枝花学院资源与环境工程学院,四川 攀枝花,617000 |
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基金项目: | 四川省科技支撑计划项目(12YZJ009);四川省教育厅项目(13za0310) |
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摘 要: | 对钛合金材料Ti6Al4V铣削加工进行有限元数值计算,结合试验设计方法构建了基于支持向量回归机(SVR)的铣削力预测模型,以材料去除率和刀具寿命为优化目标,提出一种基于支持向量回归机和带精英策略的非支配排序遗传算法(NSGA-II)的优化方法。结果表明,该方法能够获得满意的Pareto解集,为钛合金铣削参数优化提供一种新的方法,具有良好的推广价值。
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关 键 词: | 钛合金 支持向量机 NSGA-II算法 多目标优化 |
Cutting Parameters Multi-object Optimization of Titanium Alloy Milling Process Based on Support Vector Regression and NSGA-II |
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Abstract: | In this paper, the Titanium Alloy Ti6Al4V milling process is analysized by ifnite element method, a milling force prediction model was established based on Support Vector Regression (SVR), The optimization design methodology based on SVR and NSGA-II is proposed for Titanium Alloy milling process cutting parameters. The results show that this methodology has a good performance in ifnding satisfying Pareto solutions, and thus can be used in the machining process parameters optimum and other material processing ifelds. |
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Keywords: | Titanium Alloy SVR NSGA-II algorithm multi-object optimization |
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