Tackling Motion-Command-Induced Nonlinear Vibration in Manufacturing Machines Using Software Compensation

使用软件补偿解决制造机器中运动命令引起的非线性振动

• 批准号: 2054715
• 负责人: Chinedum Okwudire
• 金额: $ 41.53万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2054715&HistoricalAwards=false
• 关键词: Tackling; Motion; Command; Induced; Nonlinear

Quality, productivity and cost are three key pillars of manufacturing. To stay competitive in an increasingly global economy, U.S. manufacturers must find ways to improve the quality and productivity of their manufacturing processes while keeping costs low. Manufacturing machines tend to vibrate as they move, due to weaknesses in their mechanical structures. The resultant motion-induced vibration adversely affects the accuracy and speed of the machines, thus degrading the quality and productivity of the associated manufacturing processes. Software solutions that involve generating motion commands to avoid unwanted vibration of the machines are very attractive in practice because they are low cost. However, existing software solutions cannot adequately handle nonlinear vibrations which are prevalent in manufacturing machines like 5-axis machine tools, delta 3D printers, and robots. This award supports a scientific investigation into a software-based vibration mitigation approach that shows great promise to overcome the technical shortcomings of existing software solutions. Knowledge created through this investigation will enable industry to boost the speed and accuracy of manufacturing machines at low cost, thus increasing their competitiveness in the global marketplace. The objective of this project is to mathematically and experimentally characterize the effectiveness of optimal filtered basis functions, formulated using physics-based and data-driven linear models of nonlinearity, as a means to mitigate motion-command-induced nonlinear vibration in manufacturing machines. Three classes of nonlinearities found in manufacturing machines will be addressed. Structured nonlinearities, where nonlinear dynamics are described by first-principle equations will be tackled by designing optimal basis functions that utilize the known structure of the nonlinearities for vibration compensation. Unstructured nonlinearities, where nonlinear dynamics are described as uncertainties will be addressed by designing basis functions that are optimized for robust vibration compensation. Lastly, unknown or unmodeled nonlinearities will be addressed using a data-driven approach where vibration measured online from manufacturing machines will be used to build machine learning models to compensate vibration. The theoretical understanding and methods developed through this research will be validated experimentally on various vibration-prone manufacturing machines with nonlinearities, including a precision motion stage, a delta 3D printer, and a collaborative robot. Broader impacts of this project will be realized by: (i) cooperating with U.S.-based companies to translate the new methods to industry; (ii) educating industry and the broader public about software based vibration mitigation methods through tutorials and open-access publications; and (iii) K-12 outreach to motivate underrepresented minority students to enter STEM fields by demonstrating the benefits of software-based vibration mitigation techniques on desktop 3D printers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

质量、生产力和成本是制造业的三大支柱。为了在日益全球化的经济中保持竞争力，美国制造商必须找到提高制造过程质量和生产力的方法，同时保持低成本。由于机械结构的弱点，制造机器在移动时往往会振动。由此产生的运动引起的振动会对机器的精度和速度产生不利影响，从而降低相关制造工艺的质量和生产力。涉及生成运动命令以避免机器的不必要振动的软件解决方案在实践中非常有吸引力，因为它们成本低。然而，现有的软件解决方案无法充分处理非线性振动，这些振动在5轴机床、三角洲3D打印机和机器人等制造机器中普遍存在。该奖项支持对基于软件的减振方法进行科学研究，该方法有望克服现有软件解决方案的技术缺陷。通过这项调查创造的知识将使工业能够以低成本提高制造机器的速度和精度，从而提高其在全球市场上的竞争力。该项目的目标是从数学和实验上表征最佳滤波基函数的有效性，使用基于物理和数据驱动的非线性模型制定，作为减轻制造机器中运动命令引起的非线性振动的一种手段。三个类的非线性发现在制造机器将得到解决。结构化的非线性，其中非线性动力学描述的第一原理方程将通过设计最佳的基础函数，利用已知的结构的非线性振动补偿。非结构非线性，非线性动力学描述为不确定性将通过设计基础函数，优化鲁棒振动补偿。最后，未知或未建模的非线性将使用数据驱动的方法来解决，其中从制造机器在线测量的振动将用于构建机器学习模型以补偿振动。通过本研究开发的理论理解和方法将在各种具有非线性的易振动制造机器上进行实验验证，包括精密运动平台，delta 3D打印机和协作机器人。该项目的更广泛影响将通过以下方式实现：（一）与美国合作-（ii）通过教程和开放获取的出版物，教育行业和更广泛的公众了解基于软件的振动缓解方法;和（iii）K-12外展，通过展示软件的好处，激励代表性不足的少数民族学生进入STEM领域-该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的评估来支持。影响审查标准。

项目成果

A Generalized and Efficient Control-Oriented Modeling Approach for Vibration-Prone Delta 3D Printers Using Receptance Coupling

• DOI: 10.1109/tase.2022.3197057
• 发表时间: 2023-07
• 期刊: IEEE Transactions on Automation Science and Engineering
• 影响因子: 5.6
• 作者: Nosakhare Edoimioya;C. Okwudire

An Efficient Control-oriented Modeling Approach for Vibration-prone Delta 3D printers using Receptance Coupling

使用接收耦合为易振动 Delta 3D 打印机提供高效的面向控制的建模方法

• DOI: 10.1109/case49439.2021.9551537
• 发表时间: 2021
• 期刊: 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE
• 作者: Edoimioya, Nosakhare;Okwudire, Chinedum E.
• 通讯作者: Okwudire, Chinedum E.

Vibration compensation of delta 3D printer with position-varying dynamics using filtered B-splines

• DOI: 10.1007/s00170-022-10789-w
• 发表时间: 2022-09
• 期刊: The International Journal of Advanced Manufacturing Technology
• 作者: Nosakhare Edoimioya;Cheng-Hao Chou;C. Okwudire

A Hybrid Filtered Basis Functions Approach for Tracking Control of Linear Systems with Unmodeled Nonlinear Dynamics

具有未建模非线性动力学的线性系统跟踪控制的混合滤波基函数方法

• DOI: 10.1109/case49439.2021.9551476
• 发表时间: 2021
• 期刊: 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE
• 作者: Chou, Cheng-Hao;Duan, Molong;Okwudire, Chinedum E.
• 通讯作者: Okwudire, Chinedum E.