课题基金 / 基金详情

In-Situ Machine Axis Error Monitoring

In-Situ Machine Axis Error Monitoring
现场机器轴误差监控
批准号:
133646
负责人:
金额:
$9.9万
依托单位国家:
英国
项目类别:
Feasibility Studies
财政年份:
2018
资助国家:
英国
项目状态:
已结题
起止时间:
2018 至 --

项目摘要

项目成果

相似基金

相关文献

中文摘要
翻译
激光干涉测量通常用于测量机床轴的精度,但有一个主要缺陷,即它不能用于监测轴的动态性能,而机器正在切割。激光测量通常在静态模式下沿沿着机器轴线的固定位置进行,这意味着在进行每次测量时轴线是静止的,因此当机器处于切割部件的工作状态时,它可能不会反映机器的性能。这种低成本的原位激光监测系统将始终测量轴的位置、速度、加速度和角度,即使在机床切割时也是如此,从而确保了确定机床轴性能的最准确方法。该数据将形成更准确的补偿的基础和/或允许准确的性能/状态监测系统。来自系统的数据可以随着时间的推移进行监测,以提供机器退化信息和性能数据,用于监测生产。
英文摘要
Laser interferometry is commonly used to measure machine axis accuracy but has one major flaw in that it cannot be used to monitor axis dynamic performance while the machine is cutting. Laser measurements are typically made in static mode in fixed positions along the machine axis meaning the axis is stationary when each measurement is made so potentially it doesn't reflect the performance of the machine when it's in its working condition cutting components. This low cost in-situ laser monitoring system will measure axis position, velocity, acceleration and angle at all times even when the machine is cutting ensuring the most accurate method for determining the performance of the machine axis. This data will form the basis of more accurate compensations and/or allow an accurate performance/condition monitoring system. Data from the system can be monitored over time to provide machine degradation information and performance data for monitoring of production.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
国内基金
海外基金
Understanding structural evolution of galaxies with machine learning
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    10.0万元
  • 批准年份:
    2022
  • 负责人:
    Nicola Rosario Napolitano
  • 依托单位: