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Diagnostic and Prognostic Group Researchers Present Case Study in Prognostics and Health Management Short Course
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Diagnostic and Prognostic Group Researchers Present Case Study in Prognostics and Health Management Short Course

Chris Teubert and Shankar Sankararaman will present two modules on October 23-24 at the two-day short course, “PHM Fundamentals and Case Studies – From Monitoring/Sensing to Fault Diagnosis/Failure Prognosis and Case Studies.” The modules are: A case study on the integration process for prognostics; and a methods module on uncertainty quantification. The short course is being held in conjunction with the annual conference of the Prognostics and Health Management (PHM) Society in Coronado, California.

The prognostics case study presents an overview of the end-to-end process from requirements definition, the rigorous process of flowing down requirements, to the actual integration and operation of the capability. The case study discusses challenges resulting from differences between research and production environments and communications among key stakeholders. Two implemented examples are presented. The uncertainty quantification module focuses on explaining the significance of uncertainty in prognostics and health management applications. The module discusses how to identify and quantify the different sources of uncertainty in prognostics, and how to develop an efficient framework for overall uncertainty management. Various types of computational methods are discussed, and their application to several domains are illustrated through case studies.

BACKGROUND: The Diagnostics and Prognostics Group in the Discovery and Systems Health technical area is focused on: 1) Developing and maturing diagnostic and prognostic algorithms and uncertainty management techniques; 2) Leading the health management community in defining, standardizing, and applying metrics for measuring health-management algorithm performance; 3) Investigating component fault behavior and damage progression; and 4) Generating and disseminating data sets for validation of diagnostic and prognostic techniques. The Diagnostics and Prognostics Group has several hardware-in-the-loop testbeds in the Systems Health, Analytics, Resilience, and Physics (SHARP) lab in N269.

PROGRAM FUNDING: Shadow Mode Assessment Using Realistic Technologies for the National Airspace System (SMART-NAS) project, Airspace Operations and Safety Program (AOSP), Aeronautics Research Mission Directorate (ARMD)

COLLABORATORS: Matt Daigle (ARC) and Kai Goebel (ARC)

POC: Chris Teubert (SGT),; Shankar Sankararaman (SGT),

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