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Meeting and Seminar Archive:

Date:  January 11, 2010

Title: Distributed System Health Management

Speaker: Sankalita Saha


Abstract: As we move towards increasingly autonomous machines, it is important to understand how machines fail and if catastrophic failures can be prevented or mitigated. An important approach to tackle this problem is condition based maintenance (CBM) where various components, sub-systems and hierarchically the whole system are monitored to detect and diagnose faults and maintenance is scheduled accordingly. A key facilitating technology for this approach is prognostics, which refers to the determination of remaining useful life (RUL) of a component or a system once a fault has been detected and diagnosed. This concept is gradually gaining importance for efficient health management of systems ranging from simple machines like gearboxes to complex components like power electronics to large-scale engineered systems like automobiles, aircraft and spacecrafts. The field of prognostics and health management (PHM) comprises multiple complex problems each replete with daunting challenges. However, recent advances in sensor technologies have given us a handle on tackling some of these problems satisfactorily. In this talk, an overview of prognostics and health management will be presented first, after which a distributed wireless sensor network based architecture for such health management systems will be discussed. 



Dr. Sankalita Saha is a research scientist working at the Intelligent Systems Division at NASA Ames Research Center. She earned her PhD degree from the Electrical and Computer Engineering Department at the University of Maryland, College Park in 2007 and her bachelorís degree (Bachelor of Technology) in Electronics and Electrical Engineering from the Indian Institute of Technology, Kharagpur, India in 2002. Her current research at NASA is focused on distributed wireless sensor architectures for aircraft health management. She also works on prognostics and health management algorithms and their efficient distributed implementation.

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