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Home NILM : a comprehensive energy monitoring toolkit

Author(s)
Donnal, John Sebastian
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Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Steven B. Leeb.
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M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
In this thesis we present two powerful new non-intrusive sensor designs, one for measuring equipment power consumption and one for measuring equipment vibration. We also discuss a unified data management framework for storing, processing, and viewing the large amounts of information collected from these sensors. Our electric power sensor can detect current and voltage with no ohmic contact to the wire. This enables power measurements from previously unavailable locations such as the front of the circuit breaker or the surface of a multi wire cable. This sensor is based off a Tunneling Magnetoresistive (TMR) element which is wrapped in a novel feedback architecture to provide a linear measurement of magnetic field strength over several orders of magnitude. The vibration sensor is part of a larger embedded energy harvesting project which aims to provide diagnostic feedback on motors during operation. The management framework is a powerful collection of software programs that allows data to be collected and stored locally but efficiently manipulated remotely by users anywhere in the world.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.
 
Cataloged from PDF version of thesis.
 
Includes bibliographical references (p. 193-196).
 
Date issued
2013
URI
http://hdl.handle.net/1721.1/82386
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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