Abstract: A cyber-physical system may have a plurality of monitoring nodes each generating a series of current monitoring node values over time that represent current operation of the cyber-physical system. According to some embodiments, a features extraction computer platform may receive the series of current monitoring node values over time and generate current feature vectors based on the series of current monitoring mode values. A system mode estimation computer platform may provide the current feature vectors to a probabilistic graphical model to generate an estimated system mode. The system mode estimation computer platform may then compare the estimated system mode with a currently reported system mode output by the cyber-physical system and generate a system mode status indication based on a result of said comparison. According to some embodiments, the system mode status indication can be used to override the currently reported system mode of the cyber-physical system.

Abstract: A cyber-physical system may have a plurality of monitoring nodes each generating a series of current monitoring node values over time representing current operation of the system. A data-driven features extraction computer platform may receive the series of current monitoring node values and generate current data-driven feature vectors based on the series of current monitoring node values. A residual features extraction computer platform may receive the series of current monitoring node values, execute a system model and utilize a stochastic filter to determine current residual values, and generate current residual-driven feature vectors based on the current residual values. An abnormal detection platform may then receive the current data-driven and residual-driven feature vectors and compare the current data-driven and residual-driven feature vectors with at least one decision boundary associated with an abnormal detection model.

Abstract: A cyber-physical system may have a plurality of monitoring nodes each generating a series of current monitoring node values over time that represent current operation of the cyber-physical system. According to some embodiments, a features extraction computer platform may receive the series of current monitoring node values over time and generate current feature vectors based on the series of current monitoring mode values. A system mode estimation computer platform may provide the current feature vectors to a probabilistic graphical model to generate an estimated system mode. The system mode estimation computer platform may then compare the estimated system mode with a currently reported system mode output by the cyber-physical system and generate a system mode status indication based on a result of said comparison. According to some embodiments, the system mode status indication can be used to override the currently reported system mode of the cyber-physical system.

Abstract: A cyber-physical system may have a plurality of monitoring nodes each generating a series of current monitoring node values over time representing current operation of the system. A data-driven features extraction computer platform may receive the series of current monitoring node values and generate current data-driven feature vectors based on the series of current monitoring node values. A residual features extraction computer platform may receive the series of current monitoring node values, execute a system model and utilize a stochastic filter to determine current residual values, and generate current residual-driven feature vectors based on the current residual values. An abnormal detection platform may then receive the current data-driven and residual-driven feature vectors and compare the current data-driven and residual-driven feature vectors with at least one decision boundary associated with an abnormal detection model.

Abstract: A method for forecasting a start period for a combined cycle power generation system including a gas turbine engine, a steam turbine and a computer control system, the method including: inputting a desired time at which the power generation system is to reach a dispatchable load; inputting a current value of a predetermined operational condition of the power generation system; the computer control system retrieving historical data relating the predetermined operational condition to prior start periods of the power generation system or a similar power generation system; the computer control system executing an algorithm which generates a forecasted start time based on the desired time, current value and the retrieve data, wherein the power generation system is predicted to reach the dispatchable load at the desired time when started at the forecasted start time, and the computer system outputting the forecasted start time to the output device.

Abstract: A method for forecasting a start period for a combined cycle power generation system including a gas turbine engine, a steam turbine and a computer control system, the method including: inputting a desired time at which the power generation system is to reach a dispatchable load; inputting a current value of a predetermined operational condition of the power generation system; the computer control system retrieving historical data relating the predetermined operational condition to prior start periods of the power generation system or a similar power generation system; the computer control system executing an algorithm which generates a forecasted start time based on the desired time, current value and the retrieve data, wherein the power generation system is predicted to reach the dispatchable load at the desired time when started at the forecasted start time, and the computer system outputting the forecasted start time to the output device.

Abstract: A degradation monitoring system including: a machine; a sensor affixed to the machine, the sensors measuring a operational parameters of the machine; a set of filters receptive of information about the machine from the sensors and the filters responsively generate status signals; and comparators for comparing the status signals to stored signals, wherein the comparators indicate at least one of a presence of degradation of the machine, or a cause of degradation of the machine.

Abstract: System and method for model predictive control of a power plant. The system includes a model for a number of power plant components and the model is adapted to predict behavior of the number of power plant components. The system also includes a controller that receives inputs corresponding to operational parameters of the power plant components and improves performance criteria of the power plant according to the model. There is also provided a method for controlling a power plant.

Abstract: Embodiments of the invention relate methods to control a desalination system comprising evaluating physical models sufficient to identify physical constraints, evaluating economic models and wherein evaluating the physical and economic models provides a preliminary configuration for the desalination system to reduce the cost of water and provide operating strategies.