Andre Aboulian, Daisy H. Green , Jennifer F. Switzer , Thomas J. Kane, Gregory V. Bredariol, Peter Lindahl, John S. Donnal, and Steven B. Leeb
Nonintrusive load monitoring (NILM) uses electrical measurements taken at a centralized point in a network to monitor many loads downstream. This paper introduces NILM dashboard, a machine intelligence, and graphical platform that uses NILM data for real-time electromechanical system diagnostics. The operation of individual loads is disaggregated using signal processing and presented as time-based load activity and statistical indicators. The software allows multiple NILM devices to be networked together to provide information about loads residing on different electrical branches at the same time. A graphical user interface provides analysis tools for energy scorekeeping, detecting fault conditions, and determining operating state. The NILM dashboard is demonstrated on the power system data from two United States Coast Guard cutters.