CAREER: Algorithms for Design of Active Fault-Tolerant Systems

职业：主动容错系统设计算法

• 批准号: 0547376
• 负责人: Hod Lipson
• 金额: $ 40万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-05-01 至 2011-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0547376&HistoricalAwards=false
• 关键词: CAREER; Algorithms; Design; Active; Fault

The focus of this Faculty Early Career Development (CAREER) project is on predicting malfunction in a physical system and maintaining functionality in spite of severe faults, a common challenge in many technical fields, and of great ethical and economic importance. While traditional methods for fault-tolerance rely on passive measures such as redundancy, safety margins, and preventative maintenance, this project will develop a new active approach. This approach continuously reconstructs models of the current system from sensory data, and uses these models to assess failure and uncertainty, and to generate compensatory actions using design automation in-situ. This approach will be applied and evaluated on both quasi-static systems and dynamical systems across various scales and complexities.If successful, the broader impacts of this research will lead to improvements in the ability of systems to autonomously identify and warn about potential failure, and even sustain operation and recover from some forms of damage. As systems are becoming increasingly complex, there is a need to transition from passive fault tolerance to active fault tolerance, where systems that can diagnose and repair faults autonomously. The method proposed here is domain-independent, and as such may be applied across many complex systems beyond those explicitly addressed in the proposed work, such as modeling of biological systems and medical diagnosis.Educational activities will focus both on expansion of undergraduate curriculum in design for fault tolerance, and on a broader outreach program whose goal is to enhance hands-on engineering and science education for children and students through a library of 3D-printable educational models across several scientific fields

这个教师早期职业发展（CAREER）项目的重点是预测物理系统中的故障，并在严重故障的情况下保持功能，这是许多技术领域的共同挑战，具有重要的伦理和经济意义。传统的容错方法依赖于被动措施，如冗余、安全裕度和预防性维护，而本项目将开发一种新的主动方法。这种方法不断地从传感器数据中重建当前系统的模型，并使用这些模型来评估故障和不确定性，并使用设计自动化原位生成补偿动作。这种方法将在不同尺度和复杂性的准静态系统和动态系统上应用和评估。如果成功，这项研究的更广泛影响将导致系统自主识别和警告潜在故障的能力的提高，甚至维持运行并从某些形式的损坏中恢复。随着系统变得越来越复杂，需要从被动容错过渡到主动容错，其中系统可以自主诊断和修复故障。这里提出的方法是独立于领域的，因此可以应用于许多复杂的系统，而不是在拟议的工作中明确提出的那些系统，如生物系统建模和医疗诊断。教育活动将集中在扩展本科课程的容错设计，以及一个更广泛的推广计划，其目标是通过3D图书馆加强对儿童和学生的动手工程和科学教育，跨多个科学领域的可打印教育模型