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球头销冷镦成形工艺的逃逸粒子群优化算法
英文标题:Optimization algorithm of escaping particle swarm for ball pin cold upsetting technology
作者:葛洪央 王永乐 
单位:许昌职业技术学院 
关键词:逃逸机制 粒子群算法 球头销 成形载荷 冷镦成形 
分类号:TH162
出版年,卷(期):页码:2020,45(10):99-105
摘要:

 为了降低冷镦成形载荷、提高模具使用寿命,提出了逃逸粒子群算法的冷镦参数优化方法。介绍了球头销三维模型和冷镦工艺流程,针对球头销脱模困难的问题,设计了哈弗浮动分模来解决此问题。以减小冷镦成形载荷为优化目标,建立了参数的优化模型。依据Box-Behnken设计了27组实验,基于Deform-3D有限元软件得到了成形载荷的最大值。使用BP神经网络拟合了优化参数与成形载荷间的非线性关系,经验证BP神经网络的拟合精度较高。在粒子群算法中加入了逃逸机制,使算法具有逃出局部最优的能力,从而将参数优化问题转化为最优位置的搜索问题。经仿真验证,逃逸粒子群算法搜索到的成形载荷最大值比粒子群算法减小了11.84%;经生产验证,冷镦成形件表面光滑、成形饱满、纵向无弯曲,满足冷镦件质量要求。以上结果说明,逃逸粒子群算法搜索的参数在满足质量要求的前提下,减小了成形载荷、提高了模具使用寿命。

 In order to reduce the forming load of cold upsetting and improve the service life of mold, the optimization method of cold upsetting parameters based on escaping particle swarm algorithm was proposed, and the 3D model and the cold upsetting process flow of ball pin were introduced. Then, the Harvard floating mold was designed to solve the difficult demolding problem of ball pin. Taking reducing the forming load of cold upsetting as optimization goal, the optimized model of parameters was built. Based on Box-Behnken, twenty-seven groups of experiments were designed, and the maximum forming load was obtained by finite element software Deform-3D. Furthermore, the nonlinear relationships of optimization parameters and forming load were fit by BP neutral network, and it was verified that the fitting accuracy of BP neutral network was high. In addition, the escaping mechanism was added to particle swarm algorithm to make the algorithm have the ability to escape from local optimum, and the optimization problem of parameters was transferred into the optimal location search problem. Simulation verification results show that the maximum forming load searched by the escaping particle swarm algorithm is 11.84% less than that of the particle swarm algorithm. Finally, after production verification, the ball pin with smooth surface, full forming and no longitudinal bending meets the quality requirements of cold upsetting parts. The result indicates that through parameters searched by escaping particle swarm algorithm, the forming load is reduced, and the service life of mold is improved under the premise of meeting the quality requirement. 

基金项目:
河南省科技攻关项目(182102210508)
作者简介:
葛洪央(1967-),男,硕士,副教授 E-mail:yxrqcl@163.com
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