具有关键事件检测和材料分类的创新智能钻井

IF 3.3 Q2 ENGINEERING, MANUFACTURING
Kantawatchr Chaiprabha, R. Chanchareon
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引用次数: 0

摘要

这项工作展示了一种融合了第四次工业革命中发现的技术的网络物理钻孔机。机器的设计是通过检测是否击中或突破工件来实现其状态,除了位置传感器外,不需要额外的传感器。这种自我识别使机器能够根据工件和钻孔环境调整和移动处理位置、速度和力的控制器。在实验中,机器可以分别在0.1秒和0.5秒内检测和切换随钻事件(HIT和BREAKHTROUGH)的控制。机器的高可视性设计有利于工件材料的分类。通过在推力和进料速率上使用支持向量机(SVM),作者看到了中密度纤维板(MDF),丙烯酸和玻璃等材料分类的准确率达到92.86%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Innovative Smart Drilling with Critical Event Detection and Material Classification
This work presents a cyber-physical drilling machine that incorporates technologies discovered in the fourth industrial revolution. The machine is designed to realize its state by detecting whether it hits or breaks through the workpiece, without the need for additional sensors apart from the position sensor. Such self-recognition enables the machine to adapt and shift the controllers that handle position, velocity, and force, based on the workpiece and the drilling environment. In the experiment, the machine can detect and switch controls that follow the drilling events (HIT and BREAKHTROUGH) within 0.1 and 0.5 s, respectively. The machine’s high visibility design is beneficial for classification of the workpiece material. By using a support-vector-machine (SVM) on thrust force and feed rate, the authors are seen to achieve 92.86% accuracy for classification of material, such as medium-density fiberboard (MDF), acrylic, and glass.
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来源期刊
Journal of Manufacturing and Materials Processing
Journal of Manufacturing and Materials Processing Engineering-Industrial and Manufacturing Engineering
CiteScore
5.10
自引率
6.20%
发文量
129
审稿时长
11 weeks
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