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Massachusetts Institute of Technology

Framework of non-intrusive load monitoring for shipboard environments

Abstract

dc:description.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. 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.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2018

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Green, Daisy Hikari
Advisor dc:contributor.advisor
  • Steven B. Leeb, John S. Donnal, and Peter Lindahl.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/117820
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/117820

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Green, Daisy Hikari. Framework of non-intrusive load monitoring for shipboard environments. Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117820