Method and system for gas turbine engine simulation using adaptive Kalman filter

• US 7,742,904 B2
• Filed: 09/27/2005
• Issued: 06/22/2010
• Est. Priority Date: 09/27/2005
• Status: Active Grant

• Current Assignee: GE Infrastructure Technology, LLC (General Electric Company)
• Original Assignee: General Electric Company
• Inventors: Rosson, Randy Scott, Healy, Timothy Andrew
• Primary Examiner(s): Rodriguez; Paul L
• Assistant Examiner(s): Janakiraman; Nithya
• Application Number:
  US11/235,240
• Publication Number:
  US 20070073525A1
• Time in Patent Office: 1,729 Days
• Field of Search: 703/7, 707/100, 700/31, 700/38, 700/287, 700/290
• US Class Current: 703/7
• CPC Class Codes: G05B 13/04 involving the use of models or simulators
• CPC Class Codes: G05B 17/02 electric

Abstract

A method for simulating a gas turbine including the steps of: sensing values of a plurality of first operating parameters of an actual gas turbine; applying the sensed values of the first operating parameters to a model of the gas turbine, wherein the model generates a plurality of predicted second operating parameters; determining difference values between the predicted second operating parameters and corresponding sensed second operating parameters of the actual gas turbine; modifying the difference values based on tuning factors generated by a Kalman filter gain matrix during operation of the gas turbine, and using the adjusted difference values to adjust the model of the gas turbine. The method may further comprise generating the tuning factors by applying to the model the sensed values of the plurality of first operating parameters and perturbated values of the adjusted different values to determine optimal tuning factors.

Claims

1. A method for simulating a gas turbine comprising:

a. sensing values of a plurality of first operating parameters of an actual gas turbine;

b. applying the sensed values of the first operating parameters to a model of the gas turbine, wherein the model generates a plurality of predicted second operating parameters;

c. determining difference values between the predicted second operating parameters and corresponding sensed second operating parameters of the actual gas turbine;

d. modifying a Kalman filter gain matrix by applying to the model the sensed values of the plurality of first operating parameters and perturbated values of the difference values to determine correction factors, wherein the Kalman filter gain matrix is modified during operation of the actual gas turbine, and

e. using the correction factors to adjust the model of the gas turbine.

2. The method of claim 1 further comprising applying a third operating parameter generated by the model to control the actual gas turbine.

3. The method of claim 1 wherein the correction factors are used to generate component efficiencies and flow capacities in the model.

4. The method of claim 1 wherein the Kalman filter gain matrix is continuously generated on-line and in real-time by continuous linearization of the model of the gas turbine during operation of the actual gas turbine.

5. The method of claim 1 further comprising removing at least one of the sensed second operating values and removing the difference values corresponding to the removed at least one of the sensed second operating values, and repeating steps (c) to (e).

6. The method of claim 1 wherein the Kalman filter gain matrix includes gains applied to the difference values.

7. A method for simulating an actual gas turbine comprising:

a. sensing values of a plurality of input operating parameters of an actual gas turbine;

b. applying the sensed values of the first operating parameters to a model of the gas turbine that generates predicted values of a plurality of primary output operating parameters;

c. determining difference values by comparing the predicted values to sensed primary output operating parameters of the actual operating gas turbine;

d. applying a Kalman filter gain matrix to the difference values, wherein the Kalman filter gain matrix is generated or modified during operation of the actual gas turbine and wherein generating the Kalman filter gain matrix includes applying the sensed values of the plurality of first operating parameters and perturbated difference values to generate correction factors;

e. applying the correction factors to adjust the model of the gas turbine, wherein the model generates at least one of predicted operating parameter applied to control the actual gas turbine;

f. after step (e) removing one of the difference values and repeating steps (a) through (e).

8. The method of claim 7 wherein in step (f) the removed difference value is removed due to a sensor failure.

9. The method in claim 7 wherein the correction factors are correction factors for component efficiencies and flow capacities in the model.

10. The method of claim 7 wherein the Kalman filter gain matrix is generated in real-time during operation of the actual gas turbine.

11. The method of claim 7 wherein the Kalman filter gain matrix includes gains applied to the difference values.

12. The method as in claim 7 wherein the sensitivity is applied to determine the Kalman filter gain matrix.

13. A control and modeling system for simulating an operating gas turbine comprising:

sensors generating sensed values of a plurality of first operating parameters of the operating gas turbine;

a controller including a mathematical model of the operating gas turbine receiving the sensed values of the first operating parameters and a plurality of correction factors, wherein the model generates a plurality of predicted second operating parameters;

a comparator determining difference values between the predicted second operating parameters and corresponding sensed operation parameters of the operating gas turbine, and

said controller further generates and modifies during operation of the operating gas turbine an adaptive Kalman filter gain matrix to be applied to the difference values to generate the correction factors, wherein the Kalman filter gain matrix is generated by applying the sensed values of the plurality of first operating parameters and a series of perturbated values of the predicted second operating parameters.

14. The system of claim 13 wherein the third operating parameter is applied to control the operating gas turbine.

15. The system of claim 13 wherein the adjusted difference values are used to generate the correction factors for component efficiencies and flow capacities in the model.

16. The system of claim 13 wherein the Kalman filter gain matrix is generated in real-time during operation of the operating gas turbine.

17. The system of claim 13 wherein the controller is a computer controller for the operating gas turbine.