空心双拐曲轴内高压成形加载路径优化的研究

内高压成形技术是一种利用液体作为传力介质,通过控制内压力和轴向推力来达到成形空心零件目的的先进制造技术,在航空、航天、汽车等轻量化领域获得了广泛的应用。管材的内高压成形过程十分复杂,成形结果与诸多因素有关,其中内压力及轴向进给的加载路径及其匹配关系对成形结果影响尤为显著,如何找出诸多影响因素对内高压成形的影响规律并进行合理的优化是内高压成形面临的重要问题。首先利用均匀设计法设计BP神经网络训练样本与检测样本。其次,分析BP神经网络和遗传算法,并进行融合,基于MATLAB语言编写BP神经网络的算法程序及遗传算法程序,对空心双拐曲轴内高压成形加载路径工艺参数进行了优化,得到其最优成形参数。并通过Dyna Form软件仿真验证了结果的准确性,从而完成对管材内高压成形加载路径的参数优化,进一步提高了管材内高压成形的成形质量。

Research on Optimization of Internal High Pressure Forming Loading Path for Hollow Double Throw Crankshaft

Internal high pressure forming technology is a kind of advanced manufacturing technology that using liquid as a transmission medium,and controlling the internal pressure and axial thrust to achieve the goal of forming hollow parts.It is widely applied in lightweight fields such as aviation,aerospace,and auto.Tube internal high pressure forming process is very complex.The forming results relate to many factors.Among them,the internal pressure,the axial feed loading paths,and their matching relationship are especially significant on the forming results.How to find out the influence law of various factors affecting internal high pressure forming and to make reasonable optimization are important problems faced by internal high pressure forming technology.Uniform design method was used to design BP neural network training samples and testing samples.BP neural network and genetic algorithm were analyzed and combined.Algorithm program of BP neural network and genetic algorithm program were written based on MATLAB language.Loading path and processing parameter of hollow double throw crankshaft were optimized and the optimum forming parameters were gotten.In addition,the accuracy of the simulation result was verified with the software DynaForm.Thus,parameter optimization of loading path of tube internal high pressure forming is finished and forming quality of tube internal high pressure forming is further improved.