GOALI: Enabling Real-Time Detection and Identification of Friction Stir Welding Defects Through the Use of Physics-Based Process Dynamic Modeling

目标:通过使用基于物理的过程动态建模实现搅拌摩擦焊缺陷的实时检测和识别

基本信息

  • 批准号:
    1332738
  • 负责人:
  • 金额:
    $ 37.49万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2013
  • 资助国家:
    美国
  • 起止时间:
    2013-08-01 至 2017-07-31
  • 项目状态:
    已结题

项目摘要

This Grant Opportunities for Academic Liaison with Industry (GOALI) award provides funding for the investigation and development of a real-time defect detection approach for the material joining process known as friction stir welding. The defect detection approach will use physics-based process and defect dynamic modeling to filter or condition real-time process measurements to significantly improve the reliability of detection. The research project will develop and validate the physics-based process and defect disturbance models through a combination of process-level system identification, using both computational and experimental data, and system level validation, including verification of real-time in-situ defect detection capabilities. The project will investigate the limitations and applicability of the overall defect detection approach to include the evaluation of the sensitivity to variations in defect size and defect type and the evaluation of the robustness of the approach in the presence of non-defect related process disturbances. If successful, real-time weld defect detection would substantially reduce the total cost of friction stir welding by reducing or eliminating the need for costly post-process inspection work. In addition, the development and validation of process and defect formation models will improve our understanding of the complex solid-state friction stir welding process. The resulting reduction in cost and increase in process understanding would help accelerate its adoption as a joining process - providing the substantial economic, environmental, and energy conservation advantages that wide-spread adoption of friction stir welding and friction stir processing would bring. Finally, the project will have a strong training and mentoring focus by providing an integrated educational and research environment for graduate and undergraduate student researchers - including those in underrepresented groups through established University fellowship programs.
该奖学金为研究和开发一种用于材料连接过程的实时缺陷检测方法提供资金,这种方法被称为搅拌摩擦焊接。缺陷检测方法将使用基于物理的过程和缺陷动态建模来过滤或调节实时过程测量,以显着提高检测的可靠性。该研究项目将开发和验证基于物理的过程和缺陷干扰模型,通过结合过程级系统识别,使用计算和实验数据,以及系统级验证,包括实时原位缺陷检测能力的验证。该项目将调查整体缺陷检测方法的局限性和适用性,包括对缺陷大小和缺陷类型变化的敏感性评估,以及在存在非缺陷相关的过程干扰时对方法的鲁棒性评估。如果成功,实时焊缝缺陷检测将减少或消除昂贵的后处理检查工作,从而大大降低搅拌摩擦焊的总成本。此外,过程和缺陷形成模型的开发和验证将提高我们对复杂的固态搅拌摩擦焊接过程的理解。由此产生的成本降低和对工艺理解的增加将有助于加速其作为连接工艺的采用-提供广泛采用搅拌摩擦焊接和搅拌摩擦加工将带来的实质性经济,环境和节能优势。最后,该项目将以培训和指导为重点,为研究生和本科生研究人员提供一个综合的教育和研究环境,包括那些通过既定的大学奖学金计划代表性不足的群体。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Michael Zinn其他文献

A System for Human-Robot Teaming through End-User Programming and Shared Autonomy
通过最终用户编程和共享自治进行人机协作的系统
Can Virtual Reality Be Used to Track Skills Decay During the Research Years?
  • DOI:
    10.1016/j.jss.2019.10.030
  • 发表时间:
    2020-03-01
  • 期刊:
  • 影响因子:
  • 作者:
    Hossein Mohamadipanah;Kenneth Perrone;Katherine Peterson;Margaret Garren;Chembian Parthiban;Adhira Sunkara;Michael Zinn;Carla Pugh
  • 通讯作者:
    Carla Pugh

Michael Zinn的其他文献

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{{ truncateString('Michael Zinn', 18)}}的其他基金

NRI: Small: Interleaved Continuum-Rigid Manipulation - Enabling High-Performance and Inherent-Safety in Minimally-Invasive Surgical Procedures
NRI:小型:交错连续刚性操纵 - 在微创手术过程中实现高性能和固有安全性
  • 批准号:
    1316271
  • 财政年份:
    2013
  • 资助金额:
    $ 37.49万
  • 项目类别:
    Standard Grant

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