摘要
针对桥壳内高压成形过程的工艺参数优化进行了研究。根据桥壳零件结构的特点,确定了桥壳内高压成形的工艺过程;运用人工神经网络建模确定了工艺参数之间的关系,采用正交试验的方法分析了各项工艺参数对成形结果影响力的大小,并得到了最优工艺参数组合,即轴向位移进给量17 mm,进给时间0.1 s,液压加载峰值35.5 MPa,加载时间0.25 s。将优化后的工艺参数代入有限元模拟软件Dynaform得到数值解,验证了工艺参数优化结果的正确性,同时进行了内高压成形试验,零件轴向内高压成形的厚度值的仿真结果和试验结果误差为3.1%,径向结果误差为1.3%。试验结果与仿真结果吻合程度在合理范围内。
The optimization of process parameters in the high pressure forming process of bridge shell is studied. According to the structural characteristics of the bridge shell parts,the process of high-pressure forming in the bridge shell is determined;the relationship between the process parameters is determined by artificial neural network modeling,and the influence of each process parameter on the forming results is analyzed by orthogonal test method,and the optimal combination of process parameters is obtained,that is,the axial displacement feed amount is 17 mm,the feed time is 0. 1 s,and the hydraulic loading peak value35. 5 MPa,loading time 0. 25 s. The numerical solution is obtained by substituting the optimized process parameters into the finite element simulation software DYNAFORM, which verifies the correctness of the optimization results of the process parameters. At the same time,the internal high pressure forming test is carried out. The error between the simulation results and the test results of the thickness value of the axial internal high pressure forming is 3. 1%,and the error of the radial results is1. 3%. The agreement between the test results and the simulation results is within a reasonable range.
作者
杨靖丞
王立忠
戴晨光
YANG JingCheng;WANG LiZhong;DAI ChenGuang(School of Mechanical Engineering,Xinjiang University,Urumqi 830047,China;School of Mechanical Engineering,Xi'an Jiaotong University,Xi'an 710049,China)
出处
《机械强度》
CAS
CSCD
北大核心
2021年第3期747-751,共5页
Journal of Mechanical Strength
基金
国家自然科学地区基金项目(51865057)资助。
关键词
驱动桥壳
工艺参数优化
人工神经网络
正交试验
成形试验
Driving axle housing
Process parameter optimization
Artificial neural network
Orthogonal test
Foring test