{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/117820"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/117820","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Framework of non-intrusive load monitoring for shipboard environments","abstract":"A Non-Intrusive Load Monitor (NILM) measures power at a central point in an electrical network in order to provide real-time energy management and equipment diagnostics. Results are presented from NILM systems installed aboard two US Coast Guard ships. The collected data is used for fault diagnostics and condition-based monitoring of mission-critical systems. A NILM system requires a complex software pipeline that captures and preprocesses data, accurately disaggregates load events from the aggregate power stream, analyzes the equipment for potential faults, and presents useful information to end-users in real-time. 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This thesis presents a framework for load identification, as well as an analytical and graphical platform that provides diagnostic information to operators in real-time about the health of electromechanical systems.","abstract_has_math":false,"creators":["Green, Daisy Hikari"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Steven B. Leeb, John S. Donnal, and Peter Lindahl."],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018","date_published":"2018","updated_at":"2026-07-22T22:20:54Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["MIT theses are protected by copyright. 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