Power Management for A Distributed Wireless Health Management Architecture

Sankalita Saha, Bhaskar Saha, and Kai Goebel
Submission Type: 
Full Paper
Supporting Agencies (optional): 
NASA
AttachmentSizeTimestamp
phmc_09_42.pdf476.66 KBSeptember 17, 2009 - 11:31am

Distributed wireless architecture for prognostics is an important enabling step in prognostic research in order to achieve feasible real-time system health management. A significant problem encountered in implementation of such architectures is power management. In this paper, we present robust power management techniques for a generic health management architecture that involves diagnostics and prognostics for a system comprising multiple heterogeneous components. Our power management technique is based on online dynamic monitoring of the sensor battery discharge profile which enables accurate prediction of when the device should be put into low power mode. In our architecture, low power mode is achieved by run-time sampling rate modification through sleep states. Our experiments with a cluster of smart sensors for a hybrid diagnostics and prognostics architecture show significant gains in power management without severe loss in performance.

Publication Control Number: 
042
Submission Keywords: 
battery power management
distributed sensors
sensor network
sensors
signal processing
wireless sensor networks
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