CPS: Small: Collaborative Research: Fault Diagnosis and Prognosis in a Network of Embedded Systems in Automotive Vehicles

CPS：小型：协作研究：汽车嵌入式系统网络中的故障诊断和预测

• 批准号: 0931956
• 负责人: Krishna Pattipati
• 金额: $ 55万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0931956&HistoricalAwards=false
• 关键词: CPS; Small; Collaborative; Research; Fault

The objectives of this research are to design a heterogeneous network of embedded systems so that faults can be quickly detected and isolated and to develop on-line and off-line fault diagnosis and prognosis methods. Our approach is to develop functional dependency models between the failure modes and the concomitant monitoring mechanisms, which form the basis for failure modes, effects and criticality analysis, design for testability, diagnostic inference, and the remaining useful life estimation of (hardware) components. Over the last few years, the electronic explosion in automotive vehicles and other application domains has significantly increased the complexity, heterogeneity, and interconnectedness of embedded systems. To address the cross-subsystem malfunction phenomena in such networked systems, it is essential to develop a common methodology that: (i) identifies the potential failure modes associated with software, hardware, and hardware-software interfaces; (ii) generates functional dependencies between the failure modes and tests; (iii) provides an on-line/off-line diagnosis system; (iv) computes the remaining useful life estimates of components based on the diagnosis; and (iv) validates the diagnostic and prognostic inference methods via fault injection prior to deployment in the field. The development of functional dependency models and diagnostic inference from these models to aid in online and remote diagnosis and prognosis of embedded systems is a potentially novel aspect of this effort.This project seeks to improve the competitiveness of the U.S. automotive industry by enhancing vehicle reliability, performance and safety, and by improving customer satisfaction. Other representative applications include aerospace systems, electrification of transportation, medical equipment, and communication and power networks, to name a few.

本研究的目标是设计一个异构网络的嵌入式系统，使故障可以快速检测和隔离，并开发在线和离线故障诊断和预测方法。 我们的方法是开发功能之间的依赖关系模型的故障模式和伴随的监测机制，形成的基础上，故障模式，影响和危险性分析，设计的可测试性，诊断推理，和剩余的使用寿命估计（硬件）组件。在过去的几年里，汽车和其他应用领域的电子爆炸显着增加了嵌入式系统的复杂性，异构性和互连性。 为了解决这种网络化系统中的跨子系统故障现象，必须开发一种通用的方法：（i）识别与软件、硬件和硬件-软件接口相关的潜在故障模式;（ii）生成故障模式与测试之间的功能依赖关系;（iii）提供在线/离线诊断系统;（iv）建立故障诊断模型。（iv）基于诊断计算部件的剩余使用寿命估计;以及（iv）在现场部署之前经由故障注入验证诊断和预测推断方法。 开发功能依赖模型和诊断推理，从这些模型，以帮助在线和远程诊断和预测的嵌入式系统是一个潜在的新颖方面的努力，这个项目旨在提高美国汽车工业的竞争力，提高车辆的可靠性，性能和安全性，并通过提高客户满意度。 其他代表性应用包括航空航天系统、交通电气化、医疗设备以及通信和电力网络等。