ABSTRACT

It is very complicated to study the three-dimensional deformation of metal during rolling. The conventional finite element numerical analysis method generally adopts a fixed algorithm to calculate the whole rolling process. This method consumes huge computing power and sacrifices some computing accuracy. In this paper, according to the characteristics of different rolling stages, on the basis of considering the degree of metal deformation, a particle swarm hybrid algorithm with adaptive weight-learning factor is proposed.The Zoutendijk algorithm, Rosen algorithm, Wolfe algorithm and particle swarm hybrid algorithm are used to numerically simulate the rolling transverse thickness distribution. The accuracy of the rolling model and the particle swarm hybrid algorithm are verified. The influence of work roll edge contact and asymmetric roll bending on the deformation of rolling metal is analysed based on particle swarm mixing algorithm.

摘要

研究金属轧制过程中的三维变形非常复杂。常规的有限元数值分析方法一般采用固定的算法来计算整个轧制过程。这种方法消耗巨大的计算能力并牺牲了一定的计算精度。本文根据不同轧制阶段的特点，在考虑金属变形程度的基础上，提出了一种具有自适应权重学习因子的粒子群混合算法。Zoutendijk算法、Rosen算法、Wolfe算法和粒子群算法采用混合算法对轧制横向厚度分布进行数值模拟。验证了滚动模型和粒子群混合算法的准确性。