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Distributed wireless architectures 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 techniques are based on online dynamic monitoring of the sensor battery discharge profile which enables accurate predictions of when the device should be put into low power modes. 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.
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Title Power Management for A Distributed Wireless Health Management Architecture
revision  Date   2013-05-09T13:51:10
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dashlink
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NASA
Resource language:  [u'en-US']
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public
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individual Name {u'hasEmail': u'mailto:miryam.strautkalns@nasa.gov', u'fn': u'Miryam Strautkalns'}
organisation Name  {u'subOrganizationOf': {u'subOrganizationOf': {u'name': u'U.S. Government'}, u'name': u'National Aeronautics and Space Administration'}, u'name': u'Dashlink'}
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Metadata data stamp:  2013-05-09T13:51:10
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Metadata standard for this record:  ISO 19115:2003 - Geographic information - Metadata
standard version:  ISO 19115:2003
Metadata record identifier:  DASHLINK_731

Metadata record format is ISO19139 XML (MD_Metadata)