对点机器人的表面粗糙度进行激光硬化建模,重点研究表面粗糙度

Politehnika Pub Date : 2021-06-18 DOI:10.36978/cte.5.1.1
M. Babič
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引用次数: 1

摘要

机器学习的话题如此受欢迎,不仅是未来的趋势,也是钱潮。机器学习技术和智能系统方法在机械工程中非常流行。机器人激光表面硬化是一种最有前途的材料微观结构表面改性技术,以提高材料的耐磨性和耐腐蚀性。采用支持向量机和多元回归方法预测硬化试样的表面粗糙度。本文的目的是在不同的机器人激光单元参数下,建立点机器人激光硬化试样的粗糙度模型。
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Modeling surface roughness of point robot laser hardening, with emphasis on the surface
The topic of Machine Learning is so popular that it is not only the future trend, but also the money tide. Machine learning technique and intelligent system methods are very popular in mechanical engineering. Robot laser surface hardening is one of the most promising techniques for surface modification of the microstructure of a material to improve wear and corrosion resistance. For predicting the surface roughness of the hardened specimens, the support vector machine and multiple regression is used. The aim of this paper is to present modeling roughness of point robot laser hardened specimens with different parameters of robot laser cell.
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审稿时长
12 weeks
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