DETERMINGING ROOT CAUSE OF LOCOMOTIVE FAILURE

• US 20180312180A1
• Filed: 04/26/2017
• Published: 11/01/2018
• Est. Priority Date: 04/26/2017
• Status: Active Grant

• Current Assignee: GE Digital Holdings LLC (GE Aerospace)
• Original Assignee: General Electric Company
• Inventors: WANG, Chris J., NARAIN, Abhishek, LAKSHMIPATHY, Vikram
• Granted Patent: US 10,589,764 B2
• Time in Patent Office: Days
• CPC Class Codes: B61L 15/0072 On-board train data handling
• CPC Class Codes: B61L 15/0081 On-board diagnosis or maintenance
• CPC Class Codes: B61L 15/009 On-board display devices
• CPC Class Codes: B61L 27/57 for vehicles or trains, e.g. trackside supervision of train conditions

Abstract

The example embodiments are directed to a device and method for determining a root cause of equipment failure. In one example, the method includes storing a plurality of root causes of previous equipment failures, receiving textual data associated with a current equipment failure, determining a root cause for the current equipment failure by determining a similarity of keywords of each root cause with respect to the received textual data of the current equipment failure and selecting at least one root cause based on the determined similarities of the plurality of root causes, and displaying the at least one determined root cause for the current equipment failure via a display device. The example embodiments provide a system and method that automatically determine a root cause of equipment failure rather than rely on a subject matter expert.

Claims

1. A computing system comprising:

a storage configured to store information about a plurality of root causes of previous equipment failures including respective keywords associated with each root cause;

a network interface configured to receive textual data associated with a current equipment failure;

a processor configured to determine a root cause for the current equipment failure by determining a similarity of the keywords of each root cause with respect to the received textual data of the current equipment failure, and select at least one root cause based on the determined similarities of the plurality of root causes; and

an output configured to provide information about the at least one selected root cause for the current equipment failure for display via a display device.

2. The computing system of claim 1, wherein keywords associated with a root cause comprise keywords included in a root cause code of the root cause.

3. The computing system of claim 1, wherein the network interface is configured to receive different sources of textual data associated with the current equipment failure.

4. The computing system of claim 3, wherein the different sources of textual data comprise two or more of:

symptom descriptions, preliminary diagnosis, repair comments, material usage, and machine parameter readings, associated with the current equipment failure.

5. The computing system of claim 4, wherein the processor is further configured to process the textual data received from different sources to generate normalized textual data having a same format, prior to determining the at least one root cause of the current equipment failure.

6. The computing system of claim 1, wherein the processor is further configured to calculate a similarity score for each root cause based on a similarity between the textual data of the current equipment failure and the respective keywords of the root cause.

7. The computing system of claim 6, wherein the processor is further configured to select a root cause, from among the plurality of root causes, which has the greatest determined similarity score.

8. The computing system of claim 1, wherein the keywords of a root cause are weighted to emphasize at least one keyword that is more relevant to determining a similarity of the root cause with respect to the received textual data.

9. The computing system of claim 1, wherein the processor is configured to determine a plurality of root causes for the current equipment failure based on the similarities, and rank the plurality of determined root causes, and

the output is configured to provide information concerning the plurality of determined root causes for the current equipment failure based on the ranking for display via the display device.

10. A computer-implemented method comprising:

storing information about a plurality of root causes of previous equipment failures including respective keywords associated with each root cause;

receiving textual data associated with a current equipment failure;

determining a root cause for the current equipment failure by determining a similarity of the keywords of each root cause with respect to the received textual data of the current equipment failure and selecting at least one root cause based on the determined similarities of the plurality of root causes; and

outputting information about the at least one selected root cause for the current equipment failure for display via a display device.

11. The computer-implemented method of claim 10, wherein keywords associated with a root cause comprise keywords included in a root cause code of the root cause.

12. The computer-implemented method of claim 10, wherein the receiving comprises receiving different sources of textual data associated with the current equipment failure.

13. The computer-implemented method of claim 12, wherein the different sources of textual data comprise two or more of:

symptom descriptions, preliminary diagnosis, repair comments, material usage, and machine parameter readings, associated with the current equipment failure.

14. The computer-implemented method of claim 13, wherein the receiving further comprises processing the textual data received from different sources to generate normalized textual data having a same format, prior to determining the at least one root cause of the current equipment failure.

15. The computer-implemented method of claim 10, wherein the determining the similarity comprises calculating a similarity score for each root cause based on a similarity between the textual data of the current equipment failure and the respective keywords of the root cause.

16. The computer-implemented method of claim 15, wherein the selecting comprises selecting a root cause, from among the plurality of root causes, which has the greatest determined similarity score.

17. The computer-implemented method of claim 10, wherein the keywords of a root cause are weighted to emphasize at least one keyword that is more relevant to determining a similarity of the root cause with respect to the received textual data.

18. The computer-implemented method of claim 10, wherein the determining the root cause comprises determining a plurality of root causes for the current equipment failure based on the similarities, and ranking the plurality of determined root causes, and

the outputting comprises outputting information concerning the plurality of determined root causes for the current equipment failure based on the ranking for display via the display device.

19. A non-transitory computer readable medium having stored therein instructions that when executed cause a computer to perform a method comprising:

storing information about a plurality of root causes of previous equipment failures including respective keywords associated with each root cause;

receiving textual data associated with a current equipment failure;

determining a root cause for the current equipment failure by determining a similarity of the keywords of each root cause with respect to the received textual data of the current equipment failure and selecting at least one root cause based on the determined similarities of the plurality of root causes; and

outputting information about the at least one selected root cause for the current equipment failure for display via a display device.

20. The non-transitory computer readable medium of claim 19, wherein the determining the similarity comprises calculating a similarity score for each root cause based on a similarity between the textual data of the current equipment failure and the respective keywords of the root cause, and

the selecting comprises selecting a root cause, from among the plurality of root causes, which has the greatest determined similarity score.