图像扭曲
空白
过程(计算)
卷到卷处理
遗传算法
支持向量机
计算机科学
滚压成形
工程制图
工程类
算法
人工智能
机械工程
机器学习
操作系统
作者
Young Sup Woo,Dae-Cheol Ko,Taekyung Lee,Yangjin Kim,Ji-Eun Kim,Young Hoon Moon
出处
期刊:Journal of Manufacturing Science and Engineering-transactions of The Asme
[ASME International]
日期:2021-03-01
被引量:1
摘要
Abstract In a flexible roll-forming process, a metal blank is incrementally deformed into the desired shape with a variable cross-sectional profile by passing the blank through a series of forming rolls. Because of the combined effects of process and material parameters on the quality of the roll-formed product, the approaches used to optimize the roll-forming process have been largely based on experience and trial-and-error methods. Web warping is one of the major shape defects encountered in flexible roll forming. In this study, an optimization method was developed using support vector regression (SVR) and a genetic algorithm (GA) to reduce web warping in flexible roll forming. An SVR model was developed to predict the web-warping height, and a response surface method was used to investigate the effect of the process parameters. In the development of these predictive models, three process parameters—the forming-roll speed condition, leveling-roll height, and bend angle—were considered as the model inputs, and the web-warping height was used as the response variable. The GA used the web-warping height and the cost of the roll-forming system as the fitness function to optimize the process parameters of the flexible roll-forming process. When the flexible roll-forming process was carried out using the optimized process parameters, the obtained experimental results indicated a reduction in web warping. Hence, the feasibility of the proposed optimization method was confirmed.
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