{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/50557"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/50557","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Shipboard aggregate power monitoring","abstract":"Modem naval warships rely on vast arrays of sensor networks to evaluate the performance of mission critical systems. Although these sensor networks enable increased levels of automation, they are costly to install and to maintain. The power distribution network offers an alternative solution for tracking the performance of mission critical systems. Research conducted at Massachusetts Institute of Technology's Laboratory for Electromagnetic and Electronic Systems (LEES) has proven that the power distribution network contains vital information that can provide performance monitoring and automatic diagnostic functions. This thesis will address the issue of sensor-count reduction through the application of Non-Intrusive Load Monitoring (NILM) technology. Theoretical studies and field experiments will be presented in order to demonstrate the NILM's ability to correlate load activity with power measured from an aggregate level in the distribution system. Additionally, a critical evaluation is conducted on the current NILM configuration's ability to perform automated classification. Findings will be supported using data collected from NILMs monitoring power flow on board the U.S. Coast Guard Cutter ESCANABA (WMEC-907).","abstract_html":"Modem naval warships rely on vast arrays of sensor networks to evaluate the performance of mission critical systems. Although these sensor networks enable increased levels of automation, they are costly to install and to maintain. The power distribution network offers an alternative solution for tracking the performance of mission critical systems. Research conducted at Massachusetts Institute of Technology's Laboratory for Electromagnetic and Electronic Systems (LEES) has proven that the power distribution network contains vital information that can provide performance monitoring and automatic diagnostic functions. This thesis will address the issue of sensor-count reduction through the application of Non-Intrusive Load Monitoring (NILM) technology. Theoretical studies and field experiments will be presented in order to demonstrate the NILM's ability to correlate load activity with power measured from an aggregate level in the distribution system. Additionally, a critical evaluation is conducted on the current NILM configuration's ability to perform automated classification. Findings will be supported using data collected from NILMs monitoring power flow on board the U.S. Coast Guard Cutter ESCANABA (WMEC-907).","abstract_has_math":false,"creators":["Douglas, Keith P. (Keith Preston)"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Mechanical Engineering.","school":null,"contributors":[],"advisors":["Robert W. Cox and Steven B. Leeb."],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009","date_published":"2009","updated_at":"2026-07-22T22:22:24Z","subjects":["Mechanical Engineering."],"languages":["eng"],"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. 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Research conducted at Massachusetts Institute of Technology's Laboratory for Electromagnetic and Electronic Systems (LEES) has proven that the power distribution network contains vital information that can provide performance monitoring and automatic diagnostic functions. This thesis will address the issue of sensor-count reduction through the application of Non-Intrusive Load Monitoring (NILM) technology. Theoretical studies and field experiments will be presented in order to demonstrate the NILM's ability to correlate load activity with power measured from an aggregate level in the distribution system. Additionally, a critical evaluation is conducted on the current NILM configuration's ability to perform automated classification. Findings will be supported using data collected from NILMs monitoring power flow on board the U.S. Coast Guard Cutter ESCANABA (WMEC-907)."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Nav.E.and S.M."]},{"key":"dc:title","label":"Title","values":["Shipboard aggregate power monitoring"]}]}],"canonical_facts":{"dc:contributor.advisor":["Robert W. Cox and Steven B. Leeb."],"dc:contributor.department":["Massachusetts Institute of Technology. Dept. of Mechanical Engineering."],"dc:contributor.other":["Massachusetts Institute of Technology. Dept. of Mechanical Engineering."],"dc:creator":["Douglas, Keith P. (Keith Preston)"],"dc:date.accessioned":["2010-01-07T20:52:48Z"],"dc:date.available":["2010-01-07T20:52:48Z"],"dc:date.issued":["2009"],"dc:description":["Thesis (Nav. E. and S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.","Includes bibliographical references (p. 96-100)."],"dc:description.abstract":["Modem naval warships rely on vast arrays of sensor networks to evaluate the performance of mission critical systems. Although these sensor networks enable increased levels of automation, they are costly to install and to maintain. The power distribution network offers an alternative solution for tracking the performance of mission critical systems. Research conducted at Massachusetts Institute of Technology's Laboratory for Electromagnetic and Electronic Systems (LEES) has proven that the power distribution network contains vital information that can provide performance monitoring and automatic diagnostic functions. This thesis will address the issue of sensor-count reduction through the application of Non-Intrusive Load Monitoring (NILM) technology. Theoretical studies and field experiments will be presented in order to demonstrate the NILM's ability to correlate load activity with power measured from an aggregate level in the distribution system. Additionally, a critical evaluation is conducted on the current NILM configuration's ability to perform automated classification. Findings will be supported using data collected from NILMs monitoring power flow on board the U.S. Coast Guard Cutter ESCANABA (WMEC-907)."],"dc:description.degree":["Nav.E.and S.M."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/50557"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"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."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Mechanical Engineering."],"dc:title":["Shipboard aggregate power monitoring"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:22:24Z"}