SYSTEM AND METHOD TO ENHANCE TURBINE MONITORING WITH ENVIRONMENTAL INFORMATION

• US 20170357223A1
• Filed: 06/14/2016
• Published: 12/14/2017
• Est. Priority Date: 06/14/2016
• Status: Abandoned Application

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Jiang, Xiaomo, Scipio, Alston IIford, Ekanayake, Sanji, Hefner, Rebecca Evelyn
• Application Number:
  US15/182,324
• Publication Number:
  US 20170357223A1
• Time in Patent Office: Days
• CPC Class Codes: G05B 13/026 using a predictor
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 23/0243 model based detection method, e.g. first-principles knowledge model

Abstract

A control system for a gas turbine includes a processor. The processor configured to access data indicative of environmental conditions of a location of the gas turbine. The processor is configured to predict an occurrence of an event associated with the gas turbine based on the environmental conditions, wherein the event comprises a change in operation of the gas turbine due to the environmental conditions. The processor is configured to send a signal indicating the occurrence of the event to an electronic device.

Claims

1. A control system for a gas turbine, comprising:

a processor configured to;

access data indicative of environmental conditions of a location of the gas turbine;

predict an occurrence of an event associated with the gas turbine based on the environmental conditions, wherein the event comprises a change in operation of the gas turbine due to the environmental conditions; and

send a signal indicating the occurrence of the event to an electronic device.

2. The control system of claim 1, wherein the processor is configured to receive the environmental conditions via a cloud data server.

3. The control system of claim 2, wherein the processor is configured to receive operating parameters from sensors on the gas turbine from an on-site monitoring system at the location and separate from the cloud data server.

4. The control system of claim 1, wherein the processor is configured to send the signal to control operation of the gas turbine based on the event.

5. The control system of claim 4, wherein the atmospheric conditions comprise conditions related to weather tracked globally.

6. The control system of claim 1, wherein the environmental conditions comprise an amount of sulfur dioxide, sulfate aerosols, sea salt aerosols, atmospheric particulate matter with a diameter less than 2.5 micrometers PM_2.5, humidity, temperature, or any combination thereof in air surrounding the gas turbine.

7. The control system of claim 1, wherein the processor is configured to predict the occurrence of the event using a predictive model configured to forecast a rate of damage to at least one part of the gas turbine based on the environmental conditions.

8. The control system of claim 1, wherein the processor is configured to predict the event based on an occurrence of operating parameters of the gas turbine exceeding a threshold.

9. The control system of claim 8, wherein the processor is configured to compare the one or more rules with on-site monitoring (OSM) data and generate an alert when the OSM data violates the one or more rules.

10. A method, comprising:

accessing, via a processor, data indicative of environmental conditions of a location of the gas turbine;

predicting, via the processor, an occurrence of an event associated with the gas turbine based on the environmental conditions, wherein the event comprises a change in operation of the gas turbine due to the environmental conditions; and

sending a signal indicating the occurrence of the event to an electronic device.

11. The method of claim 10, comprising accessing the environmental conditions via a cloud data server.

12. The method of claim 10, wherein the environmental conditions comprise sulfur dioxide, sulfate aerosols, sea salt aerosols, atmospheric particulate matter with a diameter less than 2.5 micrometers PM_2.5, humidity, temperature, or any combination thereof in air surrounding the gas turbine.

13. The method of claim 10, comprising generating advisory information based on the alert that indicates one or more recommendations for corrective action.

14. The method of claim 10, comprising predicting the occurrence of the event using a predictive model configured to forecast a rate of damage to at least one part of the gas turbine based on the environmental conditions.

15. A non-transitory computer readable medium comprising instructions configured to be executed by a processor of a monitoring system, wherein the instructions comprise instructions configured to cause the processor to:

access data indicative of environmental conditions of a location of the gas turbine;

predict an occurrence of an event associated with the gas turbine based on the environmental conditions, wherein the event comprises a change in operation of the gas turbine due to the environmental conditions; and

send a signal indicating the occurrence of the event to an electronic device.

16. The non-transitory computer readable medium of claim 15, comprising instructions configured to cause the processor to access the environmental conditions via a cloud data server.

17. The non-transitory computer readable medium of claim 15, comprising instructions configured to cause the processor to access the environmental conditions that correspond to a location of the gas turbine system.

18. The non-transitory computer readable medium of claim 15, wherein the prediction based on the environmental conditions predicts the occurrence of the event based at least in part on weather forecasts.

19. The non-transitory computer readable medium of claim 15, wherein the environmental conditions comprise sulfur dioxide, sulfate aerosols, sea salt aerosols, atmospheric particulate matter with a diameter less than 2.5 micrometers PM_2.5, humidity, temperature, or any combination thereof in air surrounding the gas turbine.

20. The non-transitory computer readable medium of claim 15, comprising instructions configured to cause the processor to predict the occurrence of the event using a predictive model configured to forecast a rate of damage to at least one part of the gas turbine based on the environmental conditions.