Non-intrusive 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 (USCG) Cutters.

As crew sizes aboard maritime vessels shrink in efforts to reduce operational costs, ship operators increasingly rely on advanced monitoring systems to ensure proper operation of shipboard equipment. The nonintrusive load monitor (NILM) is an inexpensive, robust, and easy to install system useful for this task. NILMs measure power data at centralized locations in ship electric grids and disaggregate power draws of individual electric loads. This data contains information related to the health of shipboard equipment. We present a NILM-based framework for performing fault detection and isolation (FDI), with a particular emphasis on systems employing closed-loop hysteresis control. Such controllers can mask component faults, eventually leading to damaging system failure. The NILM system uses a neural network (NN) for load disaggregation and calculates operational metrics related to machinery health. We demonstrate the framework's effectiveness using data collected from two NILMs installed aboard a U.S. Coast Guard (USCG) cutter. The NILMs accurately disaggregate loads, and the diagnostic metrics provide easy distinction of several faults in the gray water disposal system. Early detection of such faults prevents costly wear and avoids catastrophic failures.

This paper describes the Sailboat Integrated Hydroelectric Generator (SIHG). This turbine is intended to be fixed to the transom of a 30–40 foot sailing vessel to produce green power for the vessel’s electrical systems. The design goal for the SIHG was the generation of a minimum of 225 watts at 6 knots and an ideal output of 400 watts at 6 knots. Power is generated by the SIHG when water moving over five turbine blades creates rotational motion, which is transferred through a gear box to a three-phase electrical generator. The three-phase electrical output is then rectified and used to recharge the boat’s battery. Presently, most sailboats of this size run their engines in order to recharge their batteries. The SIHG produces no emissions and has no operating costs. Extensive testing in the Thames River at the U.S. Coast Guard Academy in New London Connecticut produced data that was then used to determine the power output and efficiency of the SIHG at various speeds through the water. The turbine was fixed to the transom of a dinghy which was then towed behind a rigid hulled inflatable vessel to simulate a sailboat under wind power. Novel data collection methods and instrumentation were then used to gather power and drag data for the turbine at various speeds. Power output plots and efficiency curves were calculated from this data and are represented in this paper. Actual performance shows that the SIHG is capable of producing 275 watts at 6 knots and 400 watts at 8 knots. The maximum efficiency of the SIHG is calculated to be 37% and occurs when traveling through the water at a speed of 5 knots. Due to the substantial power generation at relatively low speeds, tidal applications are discussed.