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CAREER: Measurement and Predictive Dynamics of Meso-scale Milling

CAREER: Measurement and Predictive Dynamics of Meso-scale Milling
职业:细观铣削的测量和预测动力学
批准号:
0542418
负责人:
Brian Mann
金额:
$0.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-06-09 至 2008-02-29

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中文摘要
翻译
摘要目前预测铣削过程动态行为的方法受到限制,因为它们不能提供稳定性和精度的综合信息。因此,加工参数的选择通常是基于有限的信息或经验。其结果是由刀具振动产生的不必要的零件误差。当生产精密部件(如薄壁结构和微型部件)时,这些误差是一个限制因素。刀具振动严重限制了工业生产能力:1)精度降低;2)表面光洁度差;3)与不稳定相关的成本增加。尽管研究针对常规尺寸工具的这些限制,但在微型水平上动力学的差异和作用几乎尚未得到研究。本研究旨在开发传统到微型铣削动力学的分析和传感方法;这些发展将使考虑振动影响的智能机床成为可能。动态系统分析和建模工作为将控制策略集成到智能机器中提供了关键的第一步。这项研究旨在提高传统到微型加工应用的工业能力,开发监测旋转轴运动的新能力,并在微型零件生产(例如小型医疗设备和MEMS)方面取得进展。拓展和招募工作的重点是K-12学生和本科生,特别是来自传统上代表性不足的群体,具体做法是:1)通过一个动手儿童学习博物馆开展“你想成为一名工程师吗?”拓展项目;2)两个现有的UF外展计划。此外,本研究开发了增强未来研究基础设施的工具,并寻求使微型加工动力学的工业应用成为可能。
英文摘要
AbstractCurrent methods for predicting the dynamic behavior of the milling process are limited because they do not provide combined stability and accuracy information. Therefore, the selection of machining parameters is commonly based upon limited information or experience. The result is unnecessary part errors that are created from tool vibrations. These errors are a limiting factor when producing precision components (e.g. thin wall structures and miniature components). Tool vibrations impose severe limitations on industrial capability: 1) reduced accuracy; 2) a poor surface finish; and 3) increased costs which are linked to instability. Although research studies target these limitations for conventional size tools, the differences and role of dynamics at miniature levels has remained virtually unstudied. This research seeks to develop analysis and sensing methods for conventional to miniature milling dynamics; these developments will enable Smart Machine Tools that account for the effects of vibration. Dynamical system analysis and modeling efforts provide the crucial first steps for integrating control strategies into smart machines.This research seeks to advance industrial capability for conventional to miniature machining applications, develop new capabilities for monitoring rotating shaft motions, and provide advances in miniature part production (e.g. small medical devices and MEMS). Outreach and recruiting efforts focus on K-12 students and undergraduate students, particularly from traditionally underrepresented groups, through: 1) developing a "So you want to be an engineer?" outreach program with a hands-on children's learning museum; 2) two existing UF outreach programs. Furthermore, this research develops tools that enhance the infrastructure for future research and seeks to enable the industrial application of miniature machining dynamics.
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NRT-FW-HTF: NSF Traineeship in the Advancement of Surgical Technologies
  • 批准号:
    2125528
  • 项目类别:
    Standard Grant
  • 资助金额:
    $300.0万
  • 财政年份:
    2021
  • 负责人:
    Brian Mann
  • 依托单位:
Dynamical Systems Diagnostics for Intelligent Machine Tools
  • 批准号:
    2053470
  • 项目类别:
    Standard Grant
  • 资助金额:
    $35.81万
  • 财政年份:
    2021
  • 负责人:
    Brian Mann
  • 依托单位:
Collaborative Research: Tailoring Energy Flow in Magnetic Oscillator Arrays
  • 批准号:
    1300307
  • 项目类别:
    Standard Grant
  • 资助金额:
    $25.0万
  • 财政年份:
    2013
  • 负责人:
    Brian Mann
  • 依托单位:
Collaborative Proposal: Stability, Identification, and Stochastic Resonnance in Stochastic Delay Systems
  • 批准号:
    0900266
  • 项目类别:
    Standard Grant
  • 资助金额:
    $24.89万
  • 财政年份:
    2009
  • 负责人:
    Brian Mann
  • 依托单位:
国内基金
海外基金
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位: