作　　者： ; ; ; ;

机构地区： 西北工业大学机电学院现代设计与集成制造技术教育部重点实验室

出　　处： 《机械工程学报》 2011年第13期123-130,共8页

摘　　要： 根据铣削力的特点,提出用模糊系统进行铣削力建模的新方法。根据铣削力的特点和研究目的,设计钛合金铣削试验,试验在数控铣床上进行,用测力仪进行铣削力测量,由试验得到铣削力的训练数据和测试数据。在分析基本粒子群算法优缺点的基础上,将梯度下降算法嵌入基本粒子群算法形成改进粒子群算法。通过训练数据分别用梯度下降算法、基本粒子群算法和改进粒子群算法训练模糊系统,改进粒子群算法的收敛效果优于梯度下降算法和基本粒子群算法。用回归分析对铣削力进行建模,回归函数分别取为指数形式与线性全因子多项式形式,这样得到两种铣削力经验公式。用测试数据对各方法得到的模型分别进行测试,改进粒子群算法训练模糊系统的预测效果优于其他方法。预测结果验证了用改进粒子群算法训练的模糊系统进行铣削力建模是可行的。 Fuzzy system is adopted to model milling force on the basis of the characteristics of milling force and research purpose.Milling test of titanium alloy is designed and carried out on a numerical control milling machine,and milling force is measured by the dynamometer.From the test,training data and test data are obtained.After analyzing the advantages and disadvantages of basic particle swarm optimization（PSO） algorithm,gradient descent algorithm is incorporated into basic PSO algorithm to constitute an improved PSO algorithm.Using training data,fuzzy system is trained by gradient descent algorithm,basic PSO algorithm and improved PSO algorithm respectively.Results show that the improved PSO algorithm has better convergence than the other two algorithms.Two kinds of experience formula of milling force are obtained through regression analysis,regression functions are index form and linear full factor polynomial form.The models obtained by each method are tested by testing data respectively,the prediction effect of the fuzzy system trained by improved PSO algorithm is better than other methods.The prediction results show that the fuzzy system trained by improved PSO algorithm is reliable to model milling force.

关 键 词： 铣削力 模糊系统 粒子群算法 回归分析

领　　域： [自动化与计算机技术] [自动化与计算机技术] [机械工程]