Abstract: Embodiments of the present disclosure include a method for controlling a power generation system, the method including: detecting a heat distribution across a component of a power generation system from a thermal output of the component, during operation of the power generation system; calculating a projected heat distribution across the component based on a library of modeling data for the power generation system; calculating whether a difference between the heat distribution and the projected heat distribution exceeds a thermal threshold; adjusting the power generation system in response to the difference exceeding the predetermined threshold, wherein the adjusting includes modifying an operating setting of the power generation system.

Abstract: Embodiments of the present disclosure include a method for controlling a power generation system, the method including: detecting a gauge measurement of an operating parameter while visually monitoring a gauge of the power generation system during operation of the power generation system; calculating an expected value of the operating parameter based on a library of modeling data for the power generation system; calculating whether a difference between the gauge measurement of the operating parameter and the calculated expected value of the operating parameter exceeds a predetermined threshold; and adjusting the power generation system in response to the difference exceeding the predetermined threshold, wherein the adjusting includes one of calibrating the gauge or modifying an operating setting of the power generation system.

Abstract: Embodiments of the present disclosure include a method for controlling a power generation system, the method including: detecting a heat distribution across a component of a power generation system from a thermal output of the component, during operation of the power generation system; calculating a projected heat distribution across the component based on a library of modeling data for the power generation system; calculating whether a difference between the heat distribution and the projected heat distribution exceeds a thermal threshold; adjusting the power generation system in response to the difference exceeding the predetermined threshold, wherein the adjusting includes modifying an operating setting of the power generation system.

Abstract: Embodiments of the present disclosure include a method for controlling a power generation system, the method including: detecting a heat distribution across a component of a power generation system from a thermal output of the component, during operation of the power generation system; calculating a projected heat distribution across the component based on a library of modeling data for the power generation system; calculating whether a difference between the heat distribution and the projected heat distribution exceeds a thermal threshold; adjusting the power generation system in response to the difference exceeding the predetermined threshold, wherein the adjusting includes modifying an operating setting of the power generation system.

Abstract: Embodiments of the disclosure can relate to providing an integrated power plant advisor. In one embodiment, a method for providing an integrated power plant advisor can include receiving a signal associated with a failure of a power plant or a power plant component. The method can further include determining one or more root causes associated with the failure of the power plant or the power plant component. Based at least in part on operational data and training data from one or more power plants, a ranking of the one or more root causes associated with the failure of the power plant or the power plant component can be determined. The method can further include outputting the ranking via a client device. Based at least in part on the ranking, a repair or replacement strategy for the power plant or the power plant component can be identified.

Abstract: This disclosure provides systems for using failure mode ranking in an asset management system to generate asset maintenance outputs. Operational data, failure mode models, and configuration data for an asset, such as a complex electromechanical system, are related to failure prevention analytics configurations through failure mode rankings to enable the asset management system to reduce a future ranking of potential failure modes by changing the present configuration of the asset to include a recommended failure prevention analytics configuration.

Abstract: A power plant system includes a turbine system, a sensor, and a controller. The sensor is configured to collect a first set of data regarding the turbine system. The controller is configured to receive user input regarding constraints of the turbine system, a second set of data regarding the power plant system, and the first set of data. The controller is configured to determine whether a first notification is present based on a determined status and to generate a first maintenance package based on the first notification, life odometer solutions, condition monitoring solutions, and the first set of data. The controller is configured to generate a model of implementing the first maintenance package with respect to the turbine system as well as to generate a second maintenance package based on the user input, the second set of data, the first maintenance package, and the scenario model.

Abstract: A system includes a controller configured to control an operation of a turbine system, and an analytics system coupled to the controller and configured to receive inputs corresponding to the operation of the turbine system, generate an operational impact factor (OIF) value based at least in part on the inputs, generate a turbine system life prediction model configured to predict an operating life of one or more components of the turbine system based at least in part on the OIF value, and provide the OIF value to the controller to perform an action based thereon.

Abstract: A control system for a gas turbine includes a processor. The processor configured to access one or more operating parameters of the gas turbine. The operating parameters are configured to specify how the gas turbine operates. The processor is configured to predict a rate of degradation to one or more parts of a compressor of the gas turbine due to one or more effects on the parts by operating the gas turbine according to the one or more operating parameters. The processor is configured to send an alert to an electronic device based at least in part on the rate of degradation of the compressor.

Abstract: Power systems and methods of controlling power systems are disclosed. The system may include a power plant system (PPS) including a component and at least one computing device in communication with the PPS. The computing device(s) may be configured to control the PPS by performing processes including determining if an operational anomaly for the component occurred during operation of the PPS. In response to determining that the operational anomaly did not occurr, the computing device(s) may also perform processes including determining a first operational reliability of the component. In response to determining the operational anomaly occurred, the computing device(s) may also perform processes including determining a second operational reliability of the component based on the determined operational anomaly.

Abstract: A power plant system includes a turbine system, a sensor, and a controller. The sensor is configured to collect a first set of data regarding the turbine system. The controller is configured to receive user input regarding constraints of the turbine system, a second set of data regarding the power plant system, and the first set of data. The controller is configured to determine whether a first notification is present based on a determined status and to generate a first maintenance package based on the first notification, life odometer solutions, condition monitoring solutions, and the first set of data. The controller is configured to generate a model of implementing the first maintenance package with respect to the turbine system as well as to generate a second maintenance package based on the user input, the second set of data, the first maintenance package, and the scenario model.

Abstract: This disclosure provides systems for using failure mode ranking in an asset management system to generate asset maintenance outputs. Operational data, failure mode models, and configuration data for an asset, such as a complex electromechanical system, are related to failure prevention analytics configurations through failure mode rankings to enable the asset management system to reduce a future ranking of potential failure modes by changing the present configuration of the asset to include a recommended failure prevention analytics configuration.

Abstract: Various embodiments include a system having: a computing device configured to detect deformation in a manufactured component by: obtaining a post-deployment three-dimensional (3D) depiction of the manufactured component; obtaining a model of the manufactured component including: a nominal shape model indicating a nominal shape of the manufactured component prior to operational deployment, and an expected deformation model indicating expected deformation of the manufactured component after operational deployment; aligning a localized region of the manufactured component in the post-deployment 3D depiction with the localized region of the manufactured component in the nominal shape model; identifying a first set of points in the localized region not subject to deformation between the post-deployment 3D depiction and the nominal shape model; and identifying a second set of points in the localized region subject to deformation between the post-deployment 3D depiction and the nominal shape model.

Abstract: Various embodiments include a system having: a computing device configured to model deformation in a set of manufactured components by: forming a pre-exposure statistical distribution of measured coordinates describing the set of manufactured components from a pre-exposure three-dimensional (3D) depiction of a first sample of the manufactured component, and forming a post-exposure statistical distribution of measured coordinates describing the set of manufactured components from a post-exposure 3D depiction of a second sample of the manufactured component; calculating a difference between parameters of the pre-exposure statistical distribution and parameters of the post-exposure statistical distribution; and adjusting an expected deformation model for the set of manufactured components based upon the difference between parameters of the pre-exposure statistical distribution and the post-exposure statistical distribution, to model the deformation of the manufactured component.

Abstract: Embodiments of the disclosure can relate to providing an integrated power plant advisor. In one embodiment, a method for providing an integrated power plant advisor can include receiving a signal associated with a failure of a power plant or a power plant component. The method can further include determining one or more root causes associated with the failure of the power plant or the power plant component. Based at least in part on operational data and training data from one or more power plants, a ranking of the one or more root causes associated with the failure of the power plant or the power plant component can be determined. The method can further include outputting the ranking via a client device. Based at least in part on the ranking, a repair or replacement strategy for the power plant or the power plant component can be identified.

Abstract: Systems and methods for gas turbine operational impact modeling using statistical and physics-based methodologies are disclosed.

Abstract: A control system for a gas turbine includes a processor. The processor configured to access one or more operating parameters of the gas turbine. The operating parameters are configured to specify how the gas turbine operates. The processor is configured to predict a rate of degradation to one or more parts of a compressor of the gas turbine due to one or more effects on the parts by operating the gas turbine according to the one or more operating parameters. The processor is configured to send an alert to an electronic device based at least in part on the rate of degradation of the compressor.

Abstract: Systems and methods for gas turbine operational impact modeling using statistical and physics-based methodologies are disclosed.