Minimization of Force Model Uncertainty for CNC Milling Process Improvement

最小化力模型不确定性以改进数控铣削工艺

• 批准号: 0928602
• 负责人: Barry Fussell
• 金额: $ 20万
• 依托单位: University of New Hampshire
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0928602&HistoricalAwards=false
• 关键词: Minimization; Force; Model; Uncertainty; CNC

The objective of this research is to reduce the uncertainty of machining models through the use of wireless sensors embedded in the cutting tool. The approach is to investigate methods for in-situ model calibration, performed with sufficient frequency, such that model accuracy is maintained within acceptable error bounds. Methods based on cutting power, time domain force and torque signals, and frequency domain signals will be explored. New sensor technology using wireless Bluetooth transmission of tool mounted sensors will be investigated to measure cutting torque and force. Linearity, signal to noise ratios, and cross talk will be evaluated. Time synchronization of the wireless sensor data with the machine process data will be necessary to perform accurate model calibrations.If successful, this research will greatly improve the reliability of machine tools by giving them a self-knowledge of their process capabilities. Methods for decreasing model uncertainty will improve the utility of physics based models for computer numerical control process planning leading to greater part quality and higher machining efficiency. Machining strategies and cutting conditions (spindle speeds and feeds) can be chosen to appropriately reflect the current capabilities of the machine tool. Wireless sensors will be developed which will be broadly used in both industry and academic research. This project is consistent with the goals of the Manufacturing Engineering Laboratory at the National Institute of Standards and Technology and the Integrated Manufacturing Initiative, a public/private consortium of industry, academic, and government partners designed to strengthen the nation's manufacturing community.

这项研究的目的是通过使用嵌入切割工具中的无线传感器来减少加工模型的不确定性。 该方法是研究以足够频率执行的原位模型校准方法，以使模型精度保持在可接受的误差范围内。 将探索基于切割功率，时域力和扭矩信号以及频域信号的方法。 将研究使用无线蓝牙传输工具安装传感器的新传感器技术，以测量切割扭矩和力。 将评估线性性，信号与噪声比和跨谈话。 无线传感器数据与机器过程数据的时间同步需要进行准确的模型校准。如果成功，这项研究将通过使它们对过程能力的自我了解来大大提高机床的可靠性。 减少模型不确定性的方法将改善基于物理的模型用于计算机数值控制过程计划，从而提高零件质量和更高的加工效率。 可以选择加工策略和切割条件（主轴速度和进料）以适当反映机床的当前功能。 将开发无线传感器，这些传感器将在行业和学术研究中广泛使用。 该项目与国家标准技术研究所的制造工程实验室的目标以及旨在加强美国制造业社区的公共/私人联盟，学术和政府合作伙伴的综合制造计划。