基于加减速能力指标的CNC机床进给系统时域精度演化机制研究
Study on the Time Domain Precision Evolution Mechanism of CNC Machine Tool Feed Systems Based on Acceleration and Deceleration Capability Indicator
AI总结：
本文针对CNC机床进给系统时域动态精度设计方法不足的问题，提出考虑子系统耦合效应，以加减速能力为机电匹配关键指标，解耦控制参数揭示其对系统动态性能的影响机制，为优化设计提供新理论基础。
摘要：
机床进给系统对高速高精度加工日益增长的需求，使其设计方法的挑战凸显。现有方法难以在设计阶段确定是否满足动态性能要求，常导致设计过度或不足。因此，迫切需要研究直接针对时域动态精度的进给系统设计方法。进给系统的动态精度受电机、机械结构、运动过程和控制系统影响。然而，现有关于机电匹配对进给系统精度影响机制的研究常忽视控制与运动过程的作用。本文创新性地提出需考虑子系统间的耦合效应，将CNC机床进给系统的优化设计导向时域动态精度。此外，引入加减速能力作为机电匹配的关键指标。在解耦控制系统参数后，本研究阐明了在不同运动过程中机电匹配对进给系统整体动态性能的影响机制。本研究为CNC机床进给系统优化提供了新设计理念与理论基础。
英文摘要：
The escalating demand for high-speed and high-precision machining in machine tool feed system has brought to the forefront the challenge of its design method. Currently, existing methodologies struggle to ascertain compliance with dynamic performance requirements during the design phase, often resulting in either excessive or insufficient design. Therefore, there is an urgent need for research focused on feed system design methods that directly address time domain dynamic precision. The dynamic precision of the feed system is influenced by the motor, mechanical structure, motion processes, and control system. However, existing studies on the impact mechanisms of electromechanical matching on feed system precision often overlook the roles of control and motion processes. This paper innovatively proposes the need to consider the coupling effects among subsystems, directing the optimization design of CNC machine tool feed systems towards time domain dynamic precision. Furthermore, it introduces acceleration and deceleration capability as a key indicator of electromechanical matching. Following the decoupling of control system parameters, this study elucidates the influence mechanisms of electromechanical matching on the overall dynamic performance of the feed system under various motion processes. This research offers a novel design philosophy and theoretical foundation for the optimization of CNC machine tool feed systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
