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US 8,712,739 B2Granted
System and method for hybrid risk modeling of turbomachinery
AssigneeGeneral Electric Company
InventorsXiaomo Jiang, Christopher John Farral, Tong Zou
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Abstract
Systems and methods are disclosed herein for enhancing turbomachine operations. Such systems and methods include a hybrid risk model. The hybrid risk model includes a physics-based sub model and a statistical sub model. The physics-based sub model is configured to model physical components of a turbomachine. The statistical sub model is configured to model historical information of the turbomachine. The hybrid risk model is configured to calculate a turbomachine parameter.
Claims19
A system for analyzing turbomachinery comprising:
- a processor programmed to:
- execute a hybrid risk model comprising a physics-based sub model and a statistical sub model, wherein the physics-based sub model is configured to model physical components of a gas turbine system by using a life parameter (LP) function F (metal temperature Tmetal, stress σ at a location of interest of the gas turbine system, fired hours per start of the gas turbine system)=remaining time before unplanned event occurrence based on a data set, and the LP function F is used by the processor to derive a physics-based maintenance factor (MF) derivation MF=SSF*1/NLP where SSF is a stress scaling factor and NLP is a normalized LP function F, and the statistical sub model is configured to model historical information of a gas turbine unit by calculating an actual fired hours for the gas turbine unit, and wherein the processor is configured to calculate an equivalent fired hour parameter Equivalent FH=MF*FH where FH is the actual fired hours by combining the MF derivation with the actual fired hours and to transform the equivalent fired hour parameter into a probability of retirement of a component of the gas turbine unit by predicting a probability of occurrence of the unplanned event based on a current number of fired hours for the gas turbine unit.
A non-transient machine readable computer media comprising executable instructions configured to:
- retrieve a data correlative of operations of a gas turbine system;
- transform the data into an equivalent fired hour Equivalent_FH=MF*FH where FH is an actual fired hour for a gas turbine unit by executing a hybrid risk model comprising a physics-based sub model and a statistical sub model, wherein the physics-based sub model is configured to model physical components of a gas turbine system by using a life parameter (LP) function F (metal temperature Tmetal, stress σ at a location of interest of the gas turbine engine, fired hours per start of the gas turbine engine)=remaining time before unplanned event occurrence based on a data set, and wherein the LP function F is configured to derive a physics-based maintenance factor MF=SSF*1/NLP where SSF is a stress scaling factor and NLP is a normalized LP function F, and the statistical sub model is configured to analyze historical gas turbine unit information by calculating the actual fired hours for the gas turbine unit;
- and,
- transform the equivalent fired hour parameter into a probability of retirement of a component of the gas turbine unit by predicting a probability of occurrence of the unplanned event based on a current number of fired hours for the gas turbine unit.
1 more element
A method of creating and using a hybrid risk model comprising:
- retrieving a data set correlative of operations of a gas turbine system;
- transforming the data set correlative of operations by analyzing physical components of the gas turbine system to obtain a physics-based analysis by deriving a maintenance factor MF=SSF*1/NLP where SSF is a stress scaling factor and NLP is a normalized LP function F, wherein the MF is based on a life parameter (LP) function F (metal temperature Tmetal, stress σ at a location of interest of the gas turbine engine, fired hours per start of the gas turbine engine)=remaining time before unplanned event occurrence based on a data set;
- analyzing historical data of a gas turbine unit to obtain the actual fired hours for the gas turbine unit;
- integrating the physics-based analysis and the actual fired hours into a hybrid risk model comprising an equivalent fired hour parameter Equivalent_FH=MF*FH where FH is the actual fired hours by combining the MF derivation with the actual fired hours;
- and;
- transforming the equivalent fired hour parameter into a probability of retirement of a component of the gas turbine unit by predicting a probability of occurrence of the unplanned event based on a current number of fired hours for the gas turbine unit, wherein transforming the data and transforming the equivalent fired hour parameter are performed by a computing device.
3 more elements
Dependencies are inferred from the claim text.