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Automated classification of power signals

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dc.contributor.advisor Robert W. Cox and Steven B. Leeb. en_US
dc.contributor.author Proper, Ethan R. (Ethan Richard) en_US
dc.contributor.other System Design and Management Program. en_US
dc.date.accessioned 2009-03-16T19:49:55Z
dc.date.available 2009-03-16T19:49:55Z
dc.date.copyright 2008 en_US
dc.date.issued 2008 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/44842
dc.description Thesis (Nav. E.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and, (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2008. en_US
dc.description Includes bibliographical references (p. 106-107). en_US
dc.description.abstract The Non-Intrusive Load Monitor (NILM) is a device that utilizes voltage and current measurements to monitor an entire system from a single reference point. The NILM and associated software convert the V/I signal to spectral power envelopes that can be searched to determine when a transient occurs. The identification of this signal can then be determined by an expert classifier and a series of these classifications can be used to diagnose system failures or improper operation. Current NILM research conducted at Massachusetts Institute of Technology's Laboratory for Electromagnetic and Electronic Systems (LEES) is exploring the application and expansion of NILM technology for the use of monitoring shipboard systems. This thesis presents the ginzu application that implements a detect-classify-verify loop that locates the indexes of transients, identifies them using a decision-tree based expert classifier, and then generates a summary event file containing relevant information. The ginzu application provides a command-line interface between streaming preprocessed power data (PREP) and an included graphical user interface. This software was developed using thousands of hours of archived data from the Coast Guard Cutters ESCANABA (WMEC-907) and SENECA (WMEC-906). A validation of software effectiveness was conducted as the software was installed onboard ESCANABA. en_US
dc.description.statementofresponsibility by Ethan R. Proper. en_US
dc.format.extent 177 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights 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. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Mechanical Engineering. en_US
dc.subject System Design and Management Program. en_US
dc.title Automated classification of power signals en_US
dc.type Thesis en_US
dc.description.degree S.M. en_US
dc.description.degree Nav.E. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Mechanical Engineering. en_US
dc.contributor.department System Design and Management Program. en_US
dc.identifier.oclc 301591649 en_US


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