I/UCRC: Collaborative Research on Coupled Models for Prognostics and Health Management

I/UCRC：预测与健康管理耦合模型的合作研究

• 批准号: 1230840
• 负责人: Jay Lee
• 金额: $ 5.7万
• 依托单位: University of Cincinnati Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1230840&HistoricalAwards=false
• 关键词: UCRC; Collaborative; Research; Coupled; Models

The proposed research seeks to provide a comprehensive framework for how to collect and assess degradation data over the product lifecycle from design to usage phases. The proposed framework will enhance both data-driven modeling and physics-based modeling techniques outlined in previous prognostic research. By using the coupled model scheme, the requirements for data quality and complete product design information can be reduced. The scheme can be validated on a critical rotary machinery component, such as a bearing, as well as for more complex components and structures, such an electrical vehicle battery. The proposed work on developing a combined data driven and physics driven model for fault prognostication has the potential to yield significant cost reduction in manufacturing systems and processes. The work is supported by the Industry Advisory Board as well as individual industry members of the center and has the potential to extend the center?s portfolio. The center has actively involved minority and female students in its research through Research Experiences for Teachers and Undergraduates (RET and REU) projects and will continue to do so through the proposed effort.

拟议的研究旨在为如何从设计到使用阶段收集和评估产品生命周期的降解数据提供一个综合框架。所提出的框架将增强以前预后研究中概述的数据驱动建模和基于物理的建模技​​术。通过使用耦合模型方案，可以减少数据质量和完整产品设计信息的要求。该方案可以在关键的旋转机械组件（例如轴承）以及更复杂的组件和结构（例如电动车辆电池）上进行验证。为了开发组合数据驱动和物理驱动的模型以进行故障预后的拟议工作，有可能在制造系统和流程中大大降低成本。这项工作得到了行业顾问委员会以及该中心的个体行业成员的支持，并有可能扩展中心的投资组合。 该中心通过针对教师和本科生（RET和REU）项目的研究经验积极涉及少数民族和女学生，并将通过拟议的努力继续这样做。