Feedrate scheduling method for 3-PRS hybrid machine tools considering kinematic constraints

IF 9.1 1区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Haiming Zhang , Jianzhong Yang , Song Gao , Xiumei Gong , Wanqiang Zhu
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引用次数: 0

Abstract

Hybrid machine tools (HMTs), known for their fast response speed, high stiffness, and accuracy, have found wide applications in aerospace and other industries. However, maintaining stability and durability during high-speed machining necessitates careful feedrate scheduling. This study introduces a novel feedrate scheduling method for 3-prismatic-revolute-spherical (3-PRS) HMTs, ensuring that the velocities and accelerations of the drive axes remain within predefined ranges. Initially, the velocity and acceleration dynamics of the 3-PRS mechanism were scrutinized using the screw theory. Subsequently, a virtual axis programming method was introduced, transforming the HMT into a virtual double-pendulum five-axis serial machine tool. In addition, the space of the master–slave movement (SMM) concept is proposed to define the toolpath. Moreover, a strategy for constraining the tool center point rate and acceleration was devised based on the kinematic relationships between the drive axes, virtual axes, and tool center points. Simulation and experiment validated the efficacy of the feedrate scheduling method, demonstrating compliance with the kinematic constraints of the drive axes and enhanced machining efficiency.
考虑运动约束的3-PRS混合机床进给速度调度方法
混合动力机床(hmt)以其快速响应速度,高刚度和精度而闻名,在航空航天和其他行业中得到了广泛的应用。然而,在高速加工过程中保持稳定性和耐用性需要仔细的进给速度调度。提出了一种新的3-棱镜-转动-球面(3-PRS) hmt进给速度调度方法,以保证驱动轴的速度和加速度保持在预定范围内。首先,利用螺旋理论分析了3-PRS机构的速度和加速度动力学。在此基础上,提出了一种虚拟轴编程方法,将机床转化为虚拟的双摆五轴串联机床。此外,提出了主从运动空间的概念来定义刀具路径。基于驱动轴、虚拟轴和刀具中心点之间的运动关系,设计了刀具中心点速度和加速度的约束策略。仿真和实验验证了该进给速度调度方法的有效性,表明该方法符合驱动轴的运动约束,提高了加工效率。
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来源期刊
Robotics and Computer-integrated Manufacturing
Robotics and Computer-integrated Manufacturing 工程技术-工程:制造
CiteScore
24.10
自引率
13.50%
发文量
160
审稿时长
50 days
期刊介绍: The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.
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