Method and system for analyzing fault log data for diagnostics

• US 6,343,236 B1
• Filed: 04/02/1999
• Issued: 01/29/2002
• Est. Priority Date: 04/02/1999
• Status: Expired due to Term

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Varma, Anil, Roddy, Nicholas Edward, Gibson, David Richard
• Primary Examiner(s): Gordon, Paul P.
• Application Number:
  US09/285,611
• Time in Patent Office: 1,033 Days
• Field of Search: 700/78, 700/79, 700/21, 700/110, 700/174, 700/177, 714/2, 714/20, 714/25, 714/26
• US Class Current: 700/79
• CPC Class Codes: B61C 17/04 Arrangement or disposition of driving cabins, footplates or engine rooms; Ventilation thereof driving cabins and accessories B61D
• CPC Class Codes: B61C 17/12 Control gear; Arrangements for controlling locomotives from remote points in the train or when operating in multiple units control from points outside the train B61L3/00; fluid-actuated telemotors, servomotors F15B; control devices in general G05
• CPC Class Codes: G06F 11/2257 using expert systems
• CPC Class Codes: G06F 11/2268 Logging of test results

Abstract

The present invention discloses a system and method for analyzing fault log data from a malfunctioning machine. The system comprises a processor for receiving new fault log data comprising a plurality of faults from the malfunctioning machine and selecting a plurality of distinct faults from the new fault log data. The processor generates at least one distinct fault cluster from the selected plurality of distinct faults. Thereafter, the processor predicts at least one repair for at least one distinct fault cluster using a plurality of predetermined weighted repair and distinct fault cluster combinations.

Claims

1. A method for analyzing fault log data from a malfunctioning machine, comprising:

receiving new fault log data comprising a plurality of faults from the malfunctioning machine;

selecting a plurality of distinct faults from the new fault log data;

generating at least one distinct fault cluster from the plurality of distinct faults; and

predicting at least one repair for the at least one distinct fault cluster using a plurality of predetermined weighted repair and distinct fault cluster combinations.

2. The method of claim 1 wherein the at least one distinct fault cluster comprises at least one of a single distinct fault and a plurality of distinct faults.

3. The method of claim 1 wherein the at least one distinct fault cluster comprises a plurality of distinct faults.

4. The method of claim 1 wherein each of the plurality of predetermined weighted repair and distinct fault cluster combinations are generated from a plurality of cases, each case comprising a repair and plurality of distinct faults, and each of the plurality of predetermined weighted repair and distinct fault cluster combinations being assigned a weight determined by dividing the number of times the combination occurs in cases comprising related repairs by the number of times the combination occurs in the plurality of cases.

5. The method of claim 4 further comprising excluding at least one predetermined weighted repair and distinct fault cluster combination in which the assigned weight is determined by related cases which number less than a predetermined number.

6. The method of claim 4 wherein predicting the at least one repair comprises selecting at least one repair using a predetermined weighted repair and distinct fault cluster combination having an assigned weight which is greater than a predetermined threshold value.

7. The method of claim 4 wherein predicting the at least one repair comprises selecting at least one repair using the plurality of predetermined weighted repair and fault cluster combinations and adding assigned weights for distinct fault clusters for related repairs.

8. The method of claim 1 further comprising generating a plurality of predetermined weighted repair and distinct fault cluster combinations from repair data comprising a plurality of repairs and fault log data comprising a plurality of faults.

9. The method of claim 8 wherein the generating a plurality of predetermined weighted repair and distinct fault cluster combinations comprises;

generating a plurality of cases from repair data and the fault log data, each case comprising a repair and a plurality of distinct faults;

generating, for each of the plurality of cases, at least one repair and distinct fault cluster combination; and

assigning, to each of the repair and distinct fault cluster combinations, a weight, wherein the assigned weight comprises dividing the number of times the combination occurs in cases comprising related repairs by the number of times the combination occurs in the plurality of cases.

10. The method of claim 1 further comprising comparing the new fault log data to a prior fault log data.

11. The method of claim 1 wherein the new fault log data comprises a plurality of faults occurring over a predetermined period of time from the malfunctioning machine, and further comprising:

determining at least one of a completed repair and a prior recommended repair occurring during the predetermined period of time;

selecting a portion of the new fault log data which occurs after the at least one of a completed repair and a prior predicted repair;

selecting a plurality of distinct faults from the selected portion of the fault log data;

generating at least one distinct fault cluster from the selected plurality of distinct faults from the selected portion of the fault log data; and

predicting at least one repair for the at least one distinct fault cluster from the selected portion of the fault log data using a plurality of predetermined weighted repair and distinct fault cluster combinations.

12. A system for analyzing fault log data from a malfunctioning machine, comprising:

means for receiving new fault log data comprising a plurality of faults from the malfunctioning machine;

means for selecting a plurality of distinct faults from the new fault log data;

means for generating at least one distinct fault cluster from the plurality of distinct faults; and

means for predicting at least one repair for the at least one distinct fault cluster using a plurality of predetermined weighted repair and distinct fault cluster combinations.

13. The system of claim 12 wherein the at least one distinct fault cluster comprises at least one of a single distinct fault and a plurality of distinct faults.

14. The system of claim 12 wherein the at least one distinct fault cluster comprises a plurality of distinct faults.

15. The system of claim 12 wherein each of the plurality of predetermined weighted repair and distinct fault cluster combinations are generated from a plurality of cases, each case comprising a repair and plurality of distinct faults, and each of the plurality of predetermined weighted repair and distinct fault cluster combinations being assigned a weight determined by dividing the number of times the combination occurs in cases comprising related repairs by the number of times the combination occurs in the plurality of cases.

16. The system of claim 15 further comprising means for excluding predetermined weighted repair and distinct fault cluster combinations in which the assigned weight is determined by related cases which number less than a predetermined number.

17. The system of claim 15 wherein predicting the at least one repair comprises means for selecting at least one repair using a predetermined weighted repair and distinct fault cluster combination having an assigned weight which is greater than a predetermined threshold value.

18. The system of claim 15 wherein predicting the at least one repair comprises means for selecting at least one repair using the plurality of predetermined weighted repair and fault cluster combinations and adding assigned weights for distinct fault clusters for related repairs.

19. The system of claim 12 further comprising means for generating a plurality of predetermined weighted repair and distinct fault cluster combinations from repair data comprising a plurality of repairs and fault log data comprising a plurality of faults.

20. The system of claim 19 wherein the means for generating a plurality of predetermined weighted repair and distinct fault cluster combinations comprises:

means for generating a plurality of cases from repair data and the fault log data, each case comprising a repair and a plurality of distinct faults;

means for generating, for each of the plurality of cases, at least one repair and distinct fault cluster combination; and

means for assigning, to each of the repair and distinct fault cluster combinations, a weight, wherein the assigned weight comprises dividing the number of times the combination occurs in cases comprising related repairs by the number of times the combination occurs in the plurality of cases.

21. The system of claim 12 further comprising means for comparing the new fault log data to a prior fault log data.

22. The system of claim 12 wherein the new fault log data comprises a plurality of faults occurring over a predetermined period of time from the malfunctioning machine, and further comprising:

means for determining at least one of a completed repair and a prior recommended repair occurring during the predetermined period of time;

means for selecting a portion of the new fault log data which occurs after the at least one of a completed repair and a prior predicted repair;

means for selecting a plurality of distinct faults from the selected portion of the fault log data;

means for generating at least one distinct fault cluster from the selected plurality of distinct faults from the selected portion of the fault log data; and

means for predicting at least one repair for the at least one distinct fault cluster from the selected portion of the fault log data using a plurality of predetermined weighted repair and distinct fault cluster combinations.

23. A system for analyzing fault log data from a malfunctioning machine, comprising:

a directed weight data storage unit adapted to store a plurality of weighted repair and distinct fault cluster combinations;

a processor adapted to receive new fault log data comprising a plurality of faults from the malfunctioning machine;

the processor adapted to select a plurality of distinct faults from the new fault log data;

the processor adapted to generate at least one distinct fault cluster from the selected plurality of distinct faults; and

the processor adapted to predict at least one repair for the at least one distinct fault cluster using the plurality of predetermined weighted repair and distinct fault cluster combinations.

24. An article of manufacture comprising:

a computer program product comprising computer usable medium having computer readable program code means embodied therein for causing the analysis of fault log data from a malfunctioning machine, the computer readable program code means in said article of manufacture comprising;

computer readable program code means for causing a computer to receive new fault log data comprising a plurality of faults from the malfunctioning machine;

computer readable program code means for causing a computer to identify a plurality of distinct faults from the new fault log data;

computer readable program code means for causing a computer to generate at least one distinct fault cluster from the identified plurality of distinct faults; and

computer readable program code means for causing a computer to predict at least one repair for the at least one distinct fault cluster using a plurality of predetermined weighted repair and distinct fault cluster combinations.