航空铝合金薄壁件铣削加工工艺优化及有限元仿真

发布时间：2017-12-26 16:35

本文关键词：航空铝合金薄壁件铣削加工工艺优化及有限元仿真　出处：《天津工业大学》2017年硕士论文　论文类型：学位论文

【摘要】：铝合金薄壁件在铣削加工过程中容易发生变形,难以保证铣削加工后工件的加工用精度。对于这一问题,研究铣削参数优化,对于提高加工精度、保证生产效率具有重要作用。基于现代切削理论通过有限元数值模拟仿真技术、正交试验、Matlab数学回归建模能力与遗传算法的优化能力来寻找铣削四要素的最优组合,是现代化机械加工的一个重要手段。本文以航空铝合金薄壁件7075-T651为研究载体,研究了它的铣削加工过程。设计了相应的铣削加工实验,并通过BP神经网络算法求解了铣削加工变形预测的模型,基于遗传算法实现了铣削四要素的最优化解,主要的研究内容如下:1、基于金属切削加工过程的理论模型,建立热力耦合的二维正交切削有限元模型,并对模拟切削加工过程中的关键性技术进行了详细的分析。通过对切削过程的数值模拟,得到切削过程中切削力、应变和温度的变化情况,得到与实际切削加工比较相符的结果。2、利用二维有限元数值模拟的基础,建立铝合金薄壁件铣削加工的三维有限元模型仿真。对铝合金薄壁件的铣削加工过程进行了数值模拟,得到不同铣削参数下薄壁件铣削铣削力曲线图和铣削变形曲线图。3、进行了铝合金薄壁件的铣削加工实验验证,通过Kistler测力仪和Wenzel三坐标测量机分别对对铣削加工过程中的铣削力和铣削加工后的薄壁件的变形量进行测量,验证了有限元数值模拟仿真对铣削力和铣削变形的精确性,并通过Matlab的线性回归功能得到了铣削加工的铣削力经验公式。为保证加工质量可以选择较小的进给量,铣削深度,铣削宽度,选择较大的铣削速度。4、为获得最优化的铣削加工参数,利用BP神经网络算法对铣削加工参数进行训练,确定多切削参数下的BP网络加工的变形预测模型。并通过遗传算法对铣削参数进行优化,获得了更好的加工精度和更高加工效率的铣削参数。其优化参数为:铣削转速3425r/min;铣削速度412mm/min;铣削深度0.65mm;铣削宽度2.4mm。
[Abstract]:The aluminum alloy thin-walled parts are easily deformed during the milling process, and it is difficult to ensure the machining precision of the workpiece after milling. For this problem, the study of optimization of milling parameters plays an important role in improving the machining precision and ensuring the efficiency of production. Based on modern cutting theory, finding the best combination of four elements of milling is an important means of modern machining by finite-element numerical simulation, orthogonal experiment, Matlab mathematical regression modeling ability and optimization ability of genetic algorithm. This paper studies the milling process of the aluminum alloy thin-walled part 7075-T651 as the research carrier. The design of the milling of the corresponding experiments, and through the BP neural network algorithm for the prediction model for milling deformation, genetic algorithm to achieve the optimization of milling solution based on the four elements, the main research contents are as follows: 1, based on the theoretical model of metal cutting process, cutting finite element model of two-dimensional orthogonal thermal mechanical coupling is established. And the key technique to simulate the cutting process are analyzed in detail. Through the numerical simulation of cutting process, we can get the change of cutting force, strain and temperature during cutting process, and get the result that is consistent with the actual cutting process. 2. On the basis of two-dimensional finite element numerical simulation, the 3D finite element model simulation of aluminum alloy thin-walled parts milling is established. The milling process of aluminum alloy thin-walled parts is numerically simulated, and milling force curves and milling deformation curves of thin-walled parts under different milling parameters are obtained. 3, the experimental verification Aluminum Alloy milling of thin-walled workpiece, by Kistler dynamometer and Wenzel three coordinate measuring machine of thin-walled milling force of the milling process and milling after the deformation measurement, verified the simulation accuracy of the deformation simulation of milling force and milling finite element numerical, and through the Matlab linear regression function obtained the empirical equation of milling force milling. In order to guarantee the quality of processing, small feed, milling depth, milling width are selected, and larger milling speed is selected. 4, in order to get the optimal milling parameters, the BP neural network algorithm is applied to train milling parameters, and the deformation prediction model of BP network processing under multi cutting parameters is determined. The milling parameters are optimized by genetic algorithm, and the milling parameters with better machining precision and higher machining efficiency are obtained. The optimization parameters are milling speed 3425r/min, milling speed 412mm/min, milling depth 0.65mm, milling width 2.4mm.
【学位授予单位】：天津工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TG54

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