Abstract: A method for predicting an anomaly in a combustor (16) is presented. The method includes receiving signals representative of parameters in one or more combustion cans (22, 24) of the combustor, generating a plurality of patterns based on a permutation entropy window and the signals, identifying a plurality of pattern categories in the plurality of patterns, determining a permutation entropy based on the plurality of patterns and the plurality of pattern categories, and predicting an anomaly in the combustor based on the permutation entropy. The method further includes comparing the plurality of pattern categories to determined permutations of pattern categories if the anomaly is present in the combustor, and predicting a category of the anomaly based on the comparison of the plurality of pattern categories to the determined permutations of pattern categories.

Abstract: A monitoring system of a combined cycle power plant having a topping cycle performed by a gas turbine and a bottoming cycle performed by a steam turbine, the monitoring system. The monitoring system includes a processor that receives a first set of data indicating a first measurement value of an operating parameter of the combined cycle power plant. The processor determines a baseline efficiency of the process based on the first measurement value using a bottoming cycle performance (BCP) model. The processor determines a threshold based on the baseline efficiency. The processor receives a second set of data indicating a second measurement value of the operating parameter. The processor compare the threshold to an operational efficiency based on the second measurement value using the BCP model, and provides an indication of a decrease in efficiency of the process if the operational efficiency is below the threshold.

Abstract: A non-transitory computer readable medium stores instructions that are executed by a processor of a monitoring that when executed, the processor receives a state of at least one operational parameter of the turbomachinery. Then, the processor determines whether the state is within a region of accuracy of a stored record of a stored state stored in the memory. When the state is within the region of accuracy, the processor determines at least one operating condition from the stored record. Alternatively, when the state is not within the first region of accuracy, the processor stores the state as a new record in the memory.

Abstract: A non-transitory computer-readable storage medium storing one or more processor-executable instructions wherein the one or more instructions, when executed by a processor of a controller, cause acts to be performed including receiving signals representative of pressure between respective compressor blade tips and a casing of a compressor at one or more stages, generating multiple patterns based on a permutation entropy window and the signals, identifying multiple pattern categories in the multiple patterns, determining a permutation entropy based on the multiple patterns and the multiple pattern categories, predicting an anomaly in the compressor based on the permutation entropy, comparing the multiple pattern categories to determined permutations of pattern categories when an anomaly is present in the compressor, and predicting a category of the anomaly based on the comparison of the multiple pattern categories to the determined permutation of pattern categories.

Abstract: A system includes a controller coupled to an inlet bleed heat system of a compressor. The controller is configured to detect an icing condition of an inlet portion of the compressor by determining a current compressor efficiency value of the compressor, a current compressor flow value of the compressor, or any combination thereof, comparing the current compressor efficiency value to a compressor efficiency model of the compressor, the current compressor flow value to a compressor flow model of the compressor, or any combination thereof, and providing an icing indication to the inlet bleed heat system if a first difference between the current compressor efficiency value and the compressor efficiency model is greater than a first threshold, a second difference between the current compressor flow value and the compressor flow model is greater than a second threshold, or any combination thereof.

Abstract: A method for predicting an anomaly in a combustor (16) is presented. The method includes receiving signals representative of parameters in one or more combustion cans (22, 24) of the combustor, generating a plurality of patterns based on a permutation entropy window and the signals, identifying a plurality of pattern categories in the plurality of patterns, determining a permutation entropy based on the plurality of patterns and the plurality of pattern categories, and predicting an anomaly in the combustor based on the permutation entropy. The method further includes comparing the plurality of pattern categories to determined permutations of pattern categories if the anomaly is present in the combustor, and predicting a category of the anomaly based on the comparison of the plurality of pattern categories to the determined permutations of pattern categories.

Abstract: A system includes a controller coupled to an inlet bleed heat system of a compressor. The controller is configured to detect an icing condition of an inlet portion of the compressor by determining a current compressor efficiency value of the compressor, a current compressor flow value of the compressor, or any combination thereof, comparing the current compressor efficiency value to a compressor efficiency model of the compressor, the current compressor flow value to a compressor flow model of the compressor, or any combination thereof, and providing an icing indication to the inlet bleed heat system if a first difference between the current compressor efficiency value and the compressor efficiency model is greater than a first threshold, a second difference between the current compressor flow value and the compressor flow model is greater than a second threshold, or any combination thereof.

Abstract: A non-transitory computer-readable storage medium storing one or more processor-executable instructions wherein the one or more instructions, when executed by a processor of a controller, cause acts to be performed including receiving signals representative of pressure between respective compressor blade tips and a casing of a compressor at one or more stages, generating multiple patterns based on a permutation entropy window and the signals, identifying multiple pattern categories in the multiple patterns, determining a permutation entropy based on the multiple patterns and the multiple pattern categories, predicting an anomaly in the compressor based on the permutation entropy, comparing the multiple pattern categories to determined permutations of pattern categories when an anomaly is present in the compressor, and predicting a category of the anomaly based on the comparison of the multiple pattern categories to the determined permutation of pattern categories.

Abstract: A non-transitory computer readable medium stores instructions that are executed by a processor of a monitoring that when executed, the processor receives a state of at least one operational parameter of the turbomachinery. Then, the processor determines whether the state is within a region of accuracy of a stored record of a stored state stored in the memory. When the state is within the region of accuracy, the processor determines at least one operating condition from the stored record. Alternatively, when the state is not within the first region of accuracy, the processor stores the state as a new record in the memory.

Abstract: A method includes obtaining a steady state model that models a process controlled by a controller of a gas turbine. The steady state model estimates at least one output of the process based on at least one input. The method includes creating a transient model by perturbing at least one input of the steady state model to estimate the at least one output, the at least one output comprising transient characteristics of the gas turbine. The method includes adjusting a gain of the controller continuously, at predetermined intervals, or based on a requirement trigger, or any combination thereof, based on the transient model. The gain defines a response to a difference between a reference signal and a feedback signal of the controller of the gas turbine. The method includes sending the adjusted gain to the controller. The controller controls the process based on the adjusted gain.

Abstract: A monitoring system of a combined cycle power plant having a topping cycle performed by a gas turbine and a bottoming cycle performed by a steam turbine, the monitoring system. The monitoring system includes a processor that receives a first set of data indicating a first measurement value of an operating parameter of the combined cycle power plant. The processor determines a baseline efficiency of the process based on the first measurement value using a bottoming cycle performance (BCP) model. The processor determines a threshold based on the baseline efficiency. The processor receives a second set of data indicating a second measurement value of the operating parameter. The processor compare the threshold to an operational efficiency based on the second measurement value using the BCP model, and provides an indication of a decrease in efficiency of the process if the operational efficiency is below the threshold.

Abstract: A system includes a processor configured to execute an artificial neural network (ANN). The processor is configured to receive one or more operational parameters associated with an operation of a turbine system. The turbine system includes one or more combustors. The processor is further configured to analyze, via the ANN, the one or more operational parameters to determine a characteristic pattern, and to generate, via the ANN, an output based at least in part on the determined characteristic pattern. The output includes an indication of an intensity of a flame of the one or more combustors to determine a presence or an absence of the flame.

Abstract: Presented herein are turbine machines, turbine control systems, methods, and computer-readable storage devices for controlling turbines including a compressor, a combustion system, and a turbine section comprising a turbine operating at an initial turbine output while using initial parameter values for the respective control parameters of the turbine. The techniques involve, for respective selected control parameters, selecting an adjustment of the initial parameter value of the selected control parameter, and predicting a predicted turbine output of the turbine operated using the adjustment of the selected control parameter and the initial parameter values for other control parameters; comparing the predicted turbine outputs for the adjustments of the respective control parameters to select, from the control parameters, a target control parameter having a target adjustment that results in the target turbine output; and operating the turbine with the target adjustment of the target control parameter.

Abstract: A method for determining fuel splits may generally include monitoring an airflow-related parameter of a gas turbine and determining first and second reference values for the airflow-related parameter based on a combustion reference temperature. The first reference value may be associated with a first load path of the gas turbine and the second reference value may be associated with a second load path of the gas turbine. The method may also include determining first and second fuel split commands based on the combustion reference temperature. In addition, the method may include determining a fuel split value to be applied in association with a monitored value of the airflow-related parameter based at least in part on the reference values and the fuel split commands and applying the fuel split value to regulate an amount of fuel supplied to one or more fuel circuits of the gas turbine.

Abstract: A method and system for transferring between combustion modes in a gas turbine engine is provided. A processor generates data representative of an initial set of splits for providing at least one of fuel and air to at least one combustor in the gas turbine engine. A gas turbine engine model module generates data representative of at least one engine operating condition. A first split calculation module generates data representative of at least one set of active control splits to control the engine in a first combustion mode, using as an input the initial split data. A second split calculation module generates data representative of at least one set of passive control splits to control the engine in at least a second combustion mode. Transfer between combustion modes may be accomplished via use of at least one of the active control splits and the passive control splits.

Abstract: Presented herein are turbine machines, turbine control systems, methods, and computer-readable storage devices for controlling turbines including a compressor, a combustion system, and a turbine section comprising a turbine operating at an initial turbine output while using initial parameter values for the respective control parameters of the turbine. The techniques involve, for respective selected control parameters, selecting an adjustment of the initial parameter value of the selected control parameter, and predicting a predicted turbine output of the turbine operated using the adjustment of the selected control parameter and the initial parameter values for other control parameters; comparing the predicted turbine outputs for the adjustments of the respective control parameters to select, from the control parameters, a target control parameter having a target adjustment that results in the target turbine output; and operating the turbine with the target adjustment of the target control parameter.

Abstract: A method and system for transferring between combustion modes in a gas turbine engine is provided. A processor generates data representative of an initial set of splits for providing at least one of fuel and air to at least one combustor in the gas turbine engine. A gas turbine engine model module generates data representative of at least one engine operating condition. A first split calculation module generates data representative of at least one set of active control splits to control the engine in a first combustion mode, using as an input the initial split data. A second split calculation module generates data representative of at least one set of passive control splits to control the engine in at least a second combustion mode. Transfer between combustion modes may be accomplished via use of at least one of the active control splits and the passive control splits.

Abstract: A neural network-based system for monitoring a turbine compressor. In various embodiments, the neural network-based system includes: at least one computing device configured to monitor a turbine compressor by performing actions including: comparing a monitoring output from a first artificial neural network (ANN) about the turbine compressor to a monitoring output from a second, distinct ANN about the turbine compressor; and predicting a probability of a malfunction in the turbine compressor based upon the comparison of the monitoring outputs from the first ANN and the second, distinct ANN.