薄壁件铣削加工振动分析以及变形预测

发布时间：2018-07-03 18:48

本文选题：薄壁件 + 加工变形　；参考：《西南交通大学》2016年硕士论文

【摘要】：随着制造业的发展,传统的加工方式已难于满足工业的需求。高速切削(High Speed Cutting, HSC)加工技术应运而生,高速加工技术采用超硬材料刀具和磨具,利用高精度、高自动化和高柔性的制造设备,以实现提高切削速度来达到提高加工效率和加工质量,降低加工成本的目标。在航空、航天中高速切削加工技术已得到广泛的应用。但是航空、航天产品中多采用质量较轻的铝合金薄壁零件,在高速加工中极易出现振动现象,导致工件加工变形增大,难以满足加工要求。因此需要在加工前基于加工参数对工件的加工变形情况进行预测,优化加工参数,以提高加工质量和成品率。然而,实现铝合金薄壁零件的加工变形预测,存在以下几个难点：(1)基于切削参数的动态铣削力模型的构建,(2)动态切削力作用下的加工系统动力学模型的构建及系统动力学行为预测,(3)动态切削力作用下的薄壁件加工变形预测模型的构建。为解决这些问题,本文以悬臂板结构的典型薄壁件为研究对象,对薄壁件高速加工工艺系统进行了模态分析、铣削力建模、加工系统动力学建模及振动特性分析、加工变形预测建模等方面的研究。其主要内容包括以下几个方面：(1)通过分析薄壁件铣削加工工艺系统的特点,机床的刚度相对于工件和刀具较高,因此将加工工艺系统简化为工件子系统和刀具子系统。分别对工件子系统和刀具子系统进行模态分析,获取加工工艺系统振型最突出的平面,以及在该平面内的模态质量、模态阻尼和模态刚度等模态参数,为后续薄壁件加工系统动力学模型的构建提供基础。(2)提出了一种动态切削力建模方法,首先通过分析铣削机理,将切削刃的切削过程细分为切入、稳定和切出三个时间段,分别建立不同时间段切削刃的微元切削力模型,再通过分析某一瞬时参与铣削的单齿切削刃长度,将该长度上的所有微元切削力进行积分,并计算该时刻参与切削的铣刀的齿数,将所有刀齿上的切削力求和,从而建立整个刀具的动态切削力模型,然后通过铣削力、刀具和工件的振动位移关系,建立基于动态位移的铣削力模型,最后通过试验验证了该方法的正确性。(3)基于系统模态分析和动态切削力模型,通过分析铣削力与加工工艺系统振动的关系,构建了薄壁件侧壁加工工艺系统的动力学模型,用于分析加工系统的动力学特性,并基于该模型提出了一种薄壁件铣削加工颤振稳定性的预测方法,该方法采用铣削稳定性叶瓣图来判断不同切削参数条件下加工的稳定性,最后通过试验验证了模型和方法的正确性。(4)基于动态铣削力模型和颤振稳定性预测方法,构建了薄壁件加工变形预测有限元模型,实现了薄壁件加工前的变形预测,从而为薄壁件铣削加工工艺参数的优选提供支持,最后通过试验验证了该模型的正确性,并利用试验分析了薄壁件在加工过程中出现振动对加工变形的影响。通过上述四个方面对薄壁件加工过程进行的研究,建立一套完整的针对薄壁件加工变形预测的系统性方法,为提高薄壁件加工的生产率和产品的合格率,以及加工工艺参数的优化选择提供了具有指导意义的方法和结论。
[Abstract]:With the development of the manufacturing industry, the traditional processing methods have been difficult to meet the needs of the industry. High Speed Cutting (HSC) processing technology came into being. The high speed machining technology adopts super hard material tools and grinding tools, high precision, high automation and high flexible manufacturing equipment to improve the cutting speed to improve the processing efficiency. The target of rate and processing quality and reducing the cost of processing. In aerospace, high speed machining technology has been widely used in aerospace. However, aviation and aerospace products are mostly lightweight aluminum alloy thin-walled parts. The vibration phenomenon is easy to appear in high speed machining, which causes the deformation of workpiece to be increased, so it is difficult to meet the processing requirements. Therefore, it is difficult to meet the requirements of processing. It is necessary to predict the machining deformation of the workpiece on the basis of processing parameters and optimize the processing parameters to improve the processing quality and yield. However, there are several difficulties in the prediction of machining deformation of aluminum alloy thin-walled parts. (1) construction of dynamic milling force model based on cutting parameters, (2) dynamic cutting force The construction of the dynamic model of the machining system and the prediction of the dynamic behavior of the system. (3) the construction of the deformation prediction model of the thin-walled parts under the action of dynamic cutting force. In order to solve these problems, this paper takes the typical thin-walled parts of the cantilever plate structure as the research object, and carries out the modal analysis, the milling force modeling and the addition of the thin wall parts. The main contents of the system dynamics modeling, vibration characteristics analysis and processing deformation prediction modeling are as follows: (1) by analyzing the characteristics of the milling process system of thin-walled parts, the rigidity of the machine tool is higher than the workpiece and tool, so the machining process system is simplified to the workpiece system and the tool son. The modal analysis of the workpiece subsystem and the tool subsystem is carried out to obtain the most prominent plane of the vibration mode of the processing system, and the modal parameters such as modal mass, modal damping and modal stiffness in the plane, which provide the basis for the construction of the dynamic model of the subsequent thin-walled parts processing system. (2) a dynamic cutting force is proposed. By analyzing the mechanism of milling, the cutting process of the cutting edge is divided into three stages, and the cutting force model of the cutting edge in different time periods is established, and then the cutting force of the single tooth is integrated by analyzing the length of the single tooth cutting edge. By calculating the number of the teeth of the cutter at this time, the dynamic cutting force model of the whole tool is established by cutting all the cutter teeth. Then the milling force model based on the dynamic displacement is established through the relation of the milling force, the vibration displacement of the tool and the workpiece. Finally, the correctness of the method is verified through the experiment. (3) the system is based on the system. Modal analysis and dynamic cutting force model are used to analyze the relationship between the milling force and the vibration of the processing system. A dynamic model of the thin-walled part side wall processing system is constructed, which is used to analyze the dynamic characteristics of the machining system. Based on this model, a prediction method for the chatter stability of the thin-walled part milling is proposed. The method is adopted. The stability of the machining with different milling parameters is judged by milling stability. Finally, the correctness of the model and method is verified by experiments. (4) based on the dynamic milling force model and the prediction method of flutter stability, a finite element model for the deformation prediction of thin-walled parts is constructed, and the deformation prediction before the thin-walled parts processing is realized. In the end, the accuracy of the model is verified by the test, and the effect of the vibration on the machining deformation is analyzed by the experiment. A complete set of thin-walled parts processing is established through the study of the four aspects of the machining process of thin-walled parts. The systematic method of deformation prediction provides a guiding method and conclusion for improving the productivity of the thin-walled parts and the qualified rate of the products, and the optimization of the processing parameters.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TG54

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