IRES Track II: A US-France ASI for Industrial Risk Management in Active Diagnosis, Accurate Characterization, and Reliable Mitigation with Resilience

IRES Track II：美法 ASI，用于主动诊断、准确表征和具有弹性的可靠缓解方面的工业风险管理

• 批准号: 2153858
• 负责人: Wen Chen
• 金额: $ 26.92万
• 依托单位: Wayne State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2153858&HistoricalAwards=false
• 关键词: IRES; Track; II; US; France

Industrial risk management deals with quality degradation, contingency, faults, and accidents of industrial systems that bear immediate, severe, and potentially catastrophic consequences on property, personnel, communities, and the environment. This International Research Experiences for Students (IRES) Advanced Studies Institute (ASI) will train U.S. students to be well-prepared professionals in the field of industrial risk management to improve reliability and efficiency of industrial systems. This ASI’s trainees will become ambassadors to promote the critical importance of risk management, reliability, resilience, and safety of industrial systems. Additionally, this project will train highly skilled professionals with international vision and experience in this field. Through strategic outreach and recruitment, this project will further broaden opportunities and enable the participation of under-represented minorities and female students in STEM fields. Students will develop global views in their research to be conscious and innovative on advanced technology, environment, and international collaboration. The ASI will be hosted in France by a university plus a research institution noted for their work in industrial risk management, ensuring that students are immersed in a diverse and vibrant learning and research environment. This ASI will recruit 14 U.S. graduate students (28 total in two years) and provide a comprehensive two-week training program with short courses, hands-on experience, industry engagement, and international collaboration to engage students in active learning and research at the frontiers of industrial risk management. The theme of this ASI is industrial risk management with focus on advanced methodologies for active diagnosis, accurate characterization, and reliable mitigation of various industrial risks and their applications to renewable energy systems, smart grids, and autonomous systems. The institute is hosted in INSA CVL at Bourges which is an excellent French university and INRIA Lille that is a French national research institution. The topics covered in the ASI include: Active Diagnosis of Industrial Risks in the Form of Faults/Failures in Industrial Systems, Active Risk Diagnosis using Non-asymptotic Algebraic Methods, Risk Characterization in terms of Detectability in Discrete Event Systems, Analysis of Nonlinear Systems for Risk Characterization with Robotic Applications, Information-Based Risk Assessment and Mitigation of Network Systems with Applications to Renewable Energy, Reliable Mitigation of Autonomous Quad Rotors, and Risk Analysis and Mitigation Design of Homogeneous Systems.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.

工业风险管理涉及工业系统的质量下降，应急，故障和事故，这些事故对财产，人员，社区和环境造成直接，严重和潜在的灾难性后果。这个国际学生研究经验（IRES）高级研究学院（ASI）将培养美国学生成为工业风险管理领域的专业人士，以提高工业系统的可靠性和效率。这个ASI的学员将成为大使，以促进风险管理，可靠性，弹性和工业系统安全的至关重要性。此外，该项目还将培养具有国际视野和经验的高技能专业人才。通过战略推广和招聘，该项目将进一步扩大机会，使代表性不足的少数民族和女学生能够参与STEM领域。学生将在研究中发展全球视野，对先进技术，环境和国际合作有意识和创新。ASI将在法国由一所大学和一个以工业风险管理工作而闻名的研究机构主办，确保学生沉浸在多样化和充满活力的学习和研究环境中。该ASI将招募14名美国研究生（两年内共28名），并提供为期两周的综合培训计划，包括短期课程，实践经验，行业参与和国际合作，让学生积极学习和研究工业风险管理的前沿。 本次会议的主题是工业风险管理，重点关注主动诊断、准确表征和可靠缓解各种工业风险的先进方法及其在可再生能源系统、智能电网和自主系统中的应用。该研究所位于法国布尔日的INSA CVL，这是一所优秀的法国大学，INRIA里尔是法国的国家研究机构。ASI涵盖的主题包括：以工业系统故障/失效形式的工业风险主动诊断，使用非渐近代数方法的主动风险诊断，离散事件系统中可检测性方面的风险表征，机器人应用风险表征的非线性系统分析，基于信息的风险评估和网络系统的缓解与可再生能源应用，自主四旋翼的可靠缓解，以及均质系统的风险分析和缓解设计。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Simultaneous Detection and Estimation of False Data Injection Attacks in Cyber-Physical Battery Systems using a Learning Observer

• DOI: 10.1109/iccad57653.2023.10152377
• 发表时间: 2023-05
• 期刊: 2023 International Conference on Control, Automation and Diagnosis (ICCAD)
• 作者: Wen Chen;F. Lin;L. Wang