System and Method for Monitoring Hot Gas Path Hardware Life

• US 20180163639A1
• Filed: 12/14/2016
• Published: 06/14/2018
• Est. Priority Date: 12/14/2016
• Status: Active Grant

• Current Assignee: GE Infrastructure Technology, LLC (General Electric Company)
• Original Assignee: General Electric Company
• Inventors: Huang, Yimin, Zhang, Hua, Healy, Timothy Andrew, Hu, Iris Z.
• Granted Patent: US 10,641,185 B2
• Time in Patent Office: Days
• CPC Class Codes: F02C 3/04 having a turbine driving a compressor power transmission arrangements F02C7/36; control of working fluid flow F02C9/16
• CPC Class Codes: F02C 7/05 having provisions for obviating the penetration of damaging objects or particles
• CPC Class Codes: F02C 7/08 Heating air supply before combustion, e.g. by exhaust gases
• CPC Class Codes: F02C 7/228 Dividing fuel between various burners
• CPC Class Codes: F02C 9/00 Controlling gas-turbine plants; Controlling fuel supply in air- breathing jet-propulsion plants controlling air intakes F02C7/057; controlling turbines F01D; controlling compressors F04D27/00; controlling in general G05
• CPC Class Codes: F02C 9/26 Control of fuel supply F02C9/48 takes precedence; fuel valves F02C7/232
• CPC Class Codes: F02C 9/28 Regulating systems responsive to plant or ambient parameters, e.g. temperature, pressure, rotor speed F02C9/30 - F02C9/38, F02C9/44 take precedence
• CPC Class Codes: F02C 9/52 by bleeding or by-passing the working fluid
• CPC Class Codes: F02C 9/54 by throttling the working fluid, by adjusting vanes
• CPC Class Codes: F05D 2260/80 Diagnostics
• CPC Class Codes: F05D 2260/81 Modelling or simulation
• CPC Class Codes: F05D 2260/821 Parameter estimation or prediction
• CPC Class Codes: F05D 2270/11 to prolong engine life
• CPC Class Codes: F05D 2270/44 active, predictive, or anticipative
• CPC Class Codes: G05B 23/0283 Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL] preventive maintenance, i.e. planning maintenance according to the available resources without monitoring the system G06Q10/06

Abstract

A system and a method for predicting and optimizing remaining hardware life of gas turbine components. Operating parameters of the gas turbine which may impact remaining hardware life are sensed and tracked using a plurality of sensors in communication with a control system including a computing device. Remaining hardware life is predicted using a physics-based hardware lifing model. The hardware lifing model may include an output of a filtration model configured to monitor contaminants based on a pressure drop across a filter. Optimizing the remaining hardware life is achieved by the control system adjusting one or more operation settings of the gas turbine.

Claims

1. A system comprising:

a gas turbine including an inlet section, a compressor, at least one combustor, and a turbine section;

a plurality of sensors, each sensor being configured to sense an operating parameter of the gas turbine and communicate a signal indicative of the sensed operating parameter;

a control system including a computing device in electronic communication with each sensor of the plurality sensors, wherein the computing device is configured to;

receive the signals from the sensors;

track the operating parameters indicated by the received signals over time;

apply the tracked operating parameters to a physics-based hardware lifing model; and

predict remaining hardware life for one or more components of the gas turbine based on the hardware lifing model; and

the control system is configured to adjust one or more operation settings of the gas turbine based on the predicted remaining hardware life to optimize the remaining hardware life.

2. The system of claim 1, wherein the plurality of sensors includes pressure sensors deployed upstream of a filter of the inlet section and downstream of the filter of the inlet section;

and the hardware lifing model includes receiving an input to the hardware lifing model from a filtration model configured to monitor contaminants based on a pressure drop across the filter of the inlet section.

3. The system of claim 1, wherein the plurality of sensors includes at least one of a temperature sensor, a pressure sensor and a humidity sensor.

4. The system of claim 1, wherein the one or more components of the gas turbine comprise one or more hot gas path components, and the computing device is configured to adjust one or more operation settings of the gas turbine in order to prolong the remaining hardware life for the one or more hot gas path components in response to a customer requirement to prolong the hardware life.

5. The system of claim 1, wherein the one or more operation settings of the gas turbine the computing device is configured to adjust include one or more of inlet bleed heating, fuel flow, and inlet guide vane angle.

6. The system of claim 1, wherein the computing device is configured to adjust fuel flow rate.

7. The system of claim 1, wherein the computing device is configured to adjust fuel flow split between a plurality of fuel circuits within the at least one combustor.

8. The system of claim 1, wherein the one or more components of the gas turbine is one or more of a combustion liner, a transition duct, a fuel nozzle, a stationary turbine vane and a turbine blade.

9. The system of claim 1, wherein the one or more sensed operating parameters of the gas turbine includes at least one of compressor inlet temperature, compressor inlet pressure, compressor discharge temperature, compressor discharge pressure, and combustion dynamics.

10. The system of claim 9, wherein the one or more components of the gas turbine comprise one or more hot gas path components, and the computing device is configured to store at least one of a temperature history, a pressure history, and a vibration history of the one or more hot gas path components in a computer memory.

11. A method for controlling a gas turbine, comprising:

measuring a plurality of operating parameters of the gas turbine with a plurality of sensors;

receiving signals indicative of the measured operating parameters with a computing device;

tracking the operating parameters indicated by the received signals over time;

applying the tracked operating parameters to a physics-based hardware lifing model;

predicting remaining hardware life for one or more components of the gas turbine based on the hardware lifing model; and

adjusting one or more operation settings of the gas turbine based on the predicted remaining hardware life to optimize the remaining hardware life.

12. The method of claim 11, wherein the step of measuring comprises measuring pressure upstream of a filter of the inlet section and downstream of the filter of the inlet section;

the method further comprises a step of monitoring contaminants using a filtration model based on a pressure drop across the filter of the inlet section; and

the step of applying the tracked operating parameters to a physics-based hardware lifing model comprises applying an output of the filtration model to the hardware lifing model.

13. The method of claim 11, wherein the step of measuring comprises measuring at least one of temperature, pressure, and humidity.

14. The method of claim 11, wherein the one or more components of the gas turbine comprise one or more hot gas path components, and adjusting one or more operation settings of the gas turbine based on the predicted remaining hardware life to optimize the remaining hardware life comprises adjusting one or more operation settings of the gas turbine in order to prolong the remaining hardware life for one or more hot gas path components in response to a customer requirement to prolong the hardware life.

15. The method of claim 11, wherein the step of adjusting one or more operation settings of the gas turbine based on the predicted remaining hardware life to optimize the remaining hardware life comprises adjusting one or more of inlet bleed heating, fuel flow, and inlet guide vane angle.

16. The method of claim 11, wherein the step of adjusting one or more operation settings of the gas turbine based on the predicted remaining hardware life to optimize the remaining hardware life comprises adjusting fuel flow rate.

17. The method of claim 11, wherein the step of adjusting one or more operation settings of the gas turbine based on the predicted remaining hardware life to optimize the remaining hardware life comprises adjusting fuel flow split between a plurality of fuel circuits.

18. The method of claim 11, wherein the step of predicting remaining hardware life for one or more components comprises predicting remaining hardware life for one or more of a combustion liner, a transition duct, a fuel nozzle, a stationary turbine vane and a turbine blade.

19. The method of claim 11, wherein the step of measuring a plurality of operating parameters includes measuring at least one of compressor inlet temperature, compressor inlet pressure, compressor discharge temperature, compressor discharge pressure, and combustion dynamics.

20. The method of claim 11, wherein the one or more components of the gas turbine comprise one or more hot gas path components, and the step of tracking the operating parameters comprises storing at least one of a temperature history, a pressure history, and a vibration history of the one or more hot gas path components in a computer memory.