共查询到18条相似文献,搜索用时 93 毫秒
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董淑婧 《机械制造与自动化》2019,(4):75-76
为实现对汽车后钢板弹簧吊耳零件钻孔工艺加工,设计了一套液压专用自动夹具。针对工件特点,采用完全定位方案,设计了液压夹紧机构,计算了切削力和夹紧力,根据夹紧力的大小选用了液压油缸。选用了相应的钻套、钻模板,设计了夹具体。实践证明,该套夹具结构简单,能够保证加工精度,提高了加工效率。 相似文献
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夹具布局和夹紧力大小影响切削变形的大小和分布.基于遗传算法和有限元方法,提出一种夹具布局和夹紧力优化设计方法.该方法将同步优化夹具布局和夹紧力大小以及施加变夹紧力相结合,首先以加工变形最小化和变形分布最均匀为目标同步优化夹具布局和夹紧力大小,然后在优化后的夹具布局的基础上求解使得加工变形最小的变夹紧力大小.使用该方法进行底座薄壁零件的夹具优化设计,结果表明优化得到的设计优于经验设计和多目标优化方法,该方法有效地降低了加工过程中工件的变形,提高变形均匀度. 相似文献
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根据变速箱拨叉轴上圆弧槽相对位置准确、系列拨叉轴可以在一套夹具上装夹、多个零件同时加工的加工要求,设计了一种分体式气动铣床夹具。夹具采用定位块限位拨叉轴端面、燕尾面支承拨叉轴外圆的定位方式,工件外圆多点气动夹紧。通过两级增力机构,增大夹紧力。柔性传动力矩,消除了交变铣削力作用下产生的振动。依据切削力的计算选择了气缸规格。本设计实现了工件在夹具中成组布置,提高了生产效率,保证了加工质量。 相似文献
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针对企业某法兰类零件,基于夹具设计理论,完成某立式加工中心夹具的设计。采用一面两销定位,根据切削力初步计算其理论夹紧力,选用杠杆液压缸夹紧,并设计合适的夹具体,在CROE软件中完成夹具三维模型的设计。为验证夹紧力大小是否合适,通过CROE中的Simulate模块对工件进行静力分析和模态分析,探究其最大等效应力、最大变形和固有频率,从而设计出合理的加工中心夹具。 相似文献
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装夹尺寸的单一性使得传统夹具无法适合大规模现代化的汽车轮毂柔性生产。设计了一种汽车轮毂柔性加工夹具,使用旋转直线组合式液压缸作为动力源,实现夹爪对不同型号轮毂的自动定心和夹紧。建立了夹具结构的物理模型,分析了夹具的夹紧行程。从切削力作用下被加工轮毂的位置安全性、以及夹具状态下被加工轮毂和夹具的力学安全性出发,探讨了夹具与被加工轮毂间的最小夹紧力、被加工轮毂和夹具的最大夹紧力。结果表明,对于A365铝合金汽车轮毂,42CrMo超高强度钢夹具,在转速2 500 r/min,切深3 mm,工件直径609.6 mm,进给率0.5 mm/r,切削长度为500 mm的实际加工过程中,夹具设计的有效夹紧力范围为5 025.9 N~12 000 N。 相似文献
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阐述在轮毂的数控车削加工过程中,由于受到夹具的夹紧力和切削力的作用,致使工件在加工时产生变形,尺寸精度大大超差,严重时甚至工件会脱落于夹具,导致工件报废。经过本人认真研究,通过改进夹爪、调整工件夹紧位置,适当改变夹头夹紧力及优化加工工艺等,从而大大提高了加工精度和生产效率,降低了劳动强度,节约生产成本。希望以上的方法能对从事相关工作的人员有一定的借鉴作用。 相似文献
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S. W. Zhu G. F. Ding S. W. Ma K. Y. Yan S. F. Qin 《The International Journal of Advanced Manufacturing Technology》2013,67(5-8):1423-1432
In machining process, fixture is used to keep the position and orientation of a workpiece with respect to machine tool frame. However, the workpiece always cannot be at its ideal position because of the setup error and geometric inaccuracy of the locators, clamping force, cutting force, and so on. It is necessary to predict and control the workpiece locating error which will result in machining error of parts. This paper presents a prediction model of a workpiece locating error caused by the setup error and geometric inaccuracy of locaters for the fixtures with one locating surface and two locating pins. Error parameters along 6 degrees of freedom can be calculated by the proposed model and then compensated by either using the “frame transformation” function of a numerical control (NC) system or modifying NC codes in post-processing. In addition, machining error caused by the workpiece locating error can be predicted based on a multi-body system and homogeneous transfer matrix. This is meaningful to fixture design and machining process planning. Finally, a cutting test has shown that the proposed method is practicable and effective. 相似文献
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S. Selvakumar K. P. Arulshri K. P. Padmanaban K. S. K. Sasikumar 《The International Journal of Advanced Manufacturing Technology》2013,65(9-12):1573-1586
In machining fixtures, minimizing workpiece deformation due to clamping and cutting forces is essential to maintain the machining accuracy. This can be achieved by selecting the optimal location of fixturing elements such as locators and clamps. Many researches in the past decades described more efficient algorithms for fixture layout optimization. In this paper, artificial neural networks (ANN)-based algorithm with design of experiments (DOE) is proposed to design an optimum fixture layout in order to reduce the maximum elastic deformation of the workpiece caused by the clamping and machining forces acting on the workpiece while machining. Finite element method (FEM) is used to find out the maximum deformation of the workpiece for various fixture layouts. ANN is used as an optimization tool to find the optimal location of the locators and clamps. To train the ANN, sufficient sets of input and output are fed to the ANN system. The input includes the position of the locators and clamps. The output includes the maximum deformation of the workpiece for the corresponding fixture layout under the machining condition. In the testing phase, the ANN results are compared with the FEM results. After the testing process, the trained ANN is used to predict the maximum deformation for the possible fixture layouts. DOE is introduced as another optimization tool to find the solution region for all design variables to minimum deformation of the work piece. The maximum deformations of all possible fixture layouts within the solution region are predicted by ANN. Finally, the layout which shows the minimum deformation is selected as optimal fixture layout. 相似文献
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薄壁件加工变形控制快速仿真平台开发 总被引:1,自引:0,他引:1
为控制薄壁件装夹变形和加工变形,建立了集装夹优化、加工变形预测、切削参数优化及误差补偿功能为一体的快速仿真平台.在平台实现中,装夹方案的优化采用基于形位公差控制的方法,通过多种装夹方案的比较,确定优化方案.加工变形预测时考虑了前-层变形对后-层切削深度的影响,并使切削力和加工变形达到动态平衡.为获得优化切削参数,建立了以变形控制为目标的优化模型.采用有限元法计算加工变形,采用遗传算法求解优化模型.为解得优化补偿量,仿真时考虑了变形与力的耦合效应.完成了基于ABAQUS的快速仿真平台开发.以镜座零件为例进行仿真,求得了优化的装夹方案和切削参数,验证了平台的可行性. 相似文献
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B. Li S.N. Melkote 《The International Journal of Advanced Manufacturing Technology》2001,17(2):104-113
Workpiece motion arising from localised elastic deformation at fixture-workpiece contacts owing to clamping and machining
forces is known to affect significantly the workpiece location accuracy and, hence, the final part quality. This effect can
be minimised through fixture design optimisation. The clamping force is a critical design variable that can be optimised to
reduce the workpiece motion. This paper presents a new method for determining the optimun clamping forces for a multiple clamp
fixture subjected to quasu-static machining forces. The method uses elastic contact mechanics models to represent the fixture-workpiece
contact and involves the formulation and solution of a multi-objective constrained oprimisation model. The impact of clamping
force optimisation on workpiece location accuracy is analysed through examples involving a 3-2-1 type milling fixture. 相似文献