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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.
Biography:
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 bachelor’s 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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