IP Library Granted Patent US 10,823,016
Granted Patent B2
US 10,823,016 · App. 15/612,436 · Granted Nov 3, 2020

System and method for risk categorization

Inventors: Timothy Robert Collins (Greer, SC); Paul Steven Dimascio (Greer, SC)
Assignee: General Electric Company
F01K23/101F01D21/00F01K13/02G05B23/0243G05B23/0275G06Q10/0635F05D2260/81F05D2260/82F05D2270/09F05D2270/11G05B19/042
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Quick Facts
Patent No.
US 10,823,016
App. No.
15/612,436
Granted
Nov 3, 2020
Kind
B2
Abstract

In a first embodiment, a system includes a turbine system including turbomachinery, one or more processors, and a memory storing instructions. When executed by the one or more processors, the instructions are configured to cause the one or more processors to receive an operating parameter of the turbomachinery, and calculate a risk of failure for the turbomachinery based at least in part on an asset failure mode model. The instructions are also configured to cause the one or more processors to categorize the risk of failure as a selected failure indicator category of a plurality of failure indicator categories, and output the selected failure indicator category.

Claims (42)

1. A turbine system comprising:

turbomachinery;

one or more processors;

memory storing instructions that, when executed by the one or more processors, are configured to cause the one or more processors to:

receive an operating parameter of the turbomachinery;

calculate a risk of failure for the turbomachinery based at least in part on an asset failure mode model, wherein the calculated risk of failure varies based on a degree of consequence of the failure;

categorize the risk of failure as a selected failure indicator category of a plurality of failure indicator categories; and

output the selected failure indicator category.

2. The turbine system of claim 1 , wherein the instructions are configured to cause the one or more processors to:

schedule a maintenance event based at least in part on the selected failure indicator category.

3. The turbine system of claim 1 , wherein the operating parameter comprises an indication of a setting of the turbomachinery.

4. The turbine system of claim 3 , wherein the instructions are configured to cause the one or more processors to:

recommend an alternative setting of the turbomachinery that corresponds to a lower failure indicator category of the plurality of failure indicator categories.

5. The turbine system of claim 3 , wherein the setting comprises a partial load condition, a full load condition, target temperatures within the turbomachinery, blade angles, steam cycle settings, or any combination thereof.

6. The turbine system of claim 1 , wherein receiving the operating parameter comprises receiving sensor data from a sensor associated with the turbomachinery.

7. The turbine system of claim 1 , wherein the output of the selected failure indicator category comprises a visual indicator that indicates a severity of the risk of failure.

8. The turbine system of claim 1 , wherein calculating the risk of failure comprises calculating separate risks of failure at two or more intervals, categorizing the risk comprises categorizing each of the separate risks of failure, and outputting the selected failure indicator category comprises outputting indicators for each of the separate risks of failure.

9. The turbine system of claim 8 , wherein the interval is based on operating hours, number of starts, age of components of the turbomachinery, or a combination thereof.

10. The turbine system of claim 1 , wherein the asset failure mode model comprises an empirical data-based model, a physics-based model, or a combination thereof.

11. The turbine system of claim 1 , wherein the one or more processors are located in a cloud service or a combination of the cloud service and a computer local to the turbomachinery.

12. A turbine system comprising:

turbomachinery;

monitoring system comprising:

a display;

one or more processors;

memory storing instructions that, when executed by the one or more processors, are configured to cause the one or more processors to:

receive an operating parameter of the turbomachinery;

calculate a plurality of risks of failure for the turbomachinery based at least in part on an asset failure mode model, wherein the calculation of the plurality of risks of failure varies based on a degree of consequence of a respective failure of the plurality of risks of failure;

categorize at least one of the plurality of risks of failure as a selected failure indicator category of a plurality of failure indicator categories; and

cause the display of the selected failure indicator category via the display.

13. The turbine system of claim 12 , wherein the operating parameter comprises an online time of the turbomachinery, a number of starts of the turbomachinery, a geolocation of the turbomachinery, an environment of the turbomachinery, sensed values related to an operation of components of the turbomachinery, or a combination thereof.

14. The turbine system of claim 12 , wherein the plurality of risks of failure comprises a risk of failure for each of a plurality of components of the turbomachinery, a total risk of failure of the turbomachinery, a risk of failure of groups of the components of the turbomachinery, or a combination thereof.

15. The turbine system of claim 12 , wherein a scale of categorization of the plurality of risks of failure is different between components of the turbine system and the turbine system as a whole.

16. The turbine system of claim 12 , wherein the plurality of risks of failure indicates a conditional risk and/or an accumulated risk.

17. They turbine system of claim 12 , wherein a transfer function is used to calculate the plurality of risks of failure.

18. A non-transitory, tangible, and computer-readable medium having stored thereon instructions that, when executed, are configured to cause one or more processors to:

receive an operating parameter of turbomachinery;

calculate an unreliability of the turbomachinery based at least on the operating parameter;

discretize the unreliability of the turbomachinery to provide a discretized unreliability, wherein the discretized unreliability varies based on a degree of consequence of a failure of the turbomachinery; and

cause a display of the turbomachinery to display the discretized unreliability, wherein the displayed discretized unreliability communicates a risk of failure of the turbomachinery.

19. The non-transitory, tangible, and computer-readable medium of claim 18 , wherein the operating parameter comprises at least one of a number of starts of the turbomachinery, a number of operating hours of the turbomachinery, an age of the turbomachinery, or a load condition of the turbomachinery.

20. The non-transitory, tangible, and computer-readable medium of claim 18 , wherein calculation of the unreliability of the turbomachinery is based on a calculation of reliability of components of the turbomachinery.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 17, 2023
From: GENERAL ELECTRIC COMPANY
To: GE DIGITAL HOLDINGS LLC
Reel/Frame 065612/0085 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 2, 2017
From: COLLINS, TIMOTHY ROBERT; DIMASCIO, PAUL STEVEN
To: GENERAL ELECTRIC COMPANY
Reel/Frame 042576/0416 →
Continuity (1)
Related Publication 20180347408A1 · Dec 6, 2018