Fault diagnosis system

• US 7,246,039 B2
• Filed: 07/15/2003
• Issued: 07/17/2007
• Est. Priority Date: 07/19/2002
• Status: Expired due to Fees

• Current Assignee: Selex Communications Limited (Leonardo S.p.A.)
• Original Assignee: Selex Communications Limited (Leonardo S.p.A.)
• Inventors: Moorhouse, Timothy James
• Primary Examiner(s): Barlow; John
• Assistant Examiner(s): Charioui; Mohamed
• Application Number:
  US10/474,229
• Publication Number:
  US 20050114743A1
• Time in Patent Office: 1,463 Days
• Field of Search: 702/58, 702/59, 702/119, 702/179, 702/181, 702/182, 702/183, 702/184, 702/185, 702/196, 706/9, 706/21, 706 50- 52, 706/56, 714/25, 714/26, 714/31, 714/48, 714/49
• US Class Current: 702/185
• CPC Class Codes: H04L 41/06 Management of faults, events, alarms or notifications
• CPC Class Codes: H04L 41/16 using machine learning or artificial intelligence
• CPC Class Codes: H04L 41/22 comprising specially adapted graphical user interfaces [GUI]

Abstract

A fault diagnosis system for diagnosing faults in complex equipment. The system includes means for storing a set of diagnostic signatures which relates a set of known faults which may occur in the equipment to respective fault symptoms which are deemed indicative of said known faults; and means for processing the diagnostic signatures and a set of fault symptoms identified for a current state of the equipment to calculate diagnostic data for identifying a fault causing the current state of the equipment. The diagnostic data includes a plurality of values which are indicative of different relative non-zero likelihoods of each of a plurality of different known faults causing the current state of the equipment.

Claims

1. A fault diagnosis system for diagnosing faults in complex equipment, the system including:

means for storing a set of diagnostic signatures which relates a set of known faults which may occur in the equipment to respective fault symptoms which are deemed indicative of said known faults; and

means for processing said diagnostic signatures and a set of fault symptoms identified for a current state of the equipment, to calculate diagnostic data for identifying a fault causing the current state of the equipment, the diagnostic data including a plurality of values which are indicative of different relative non-zero likelihoods of each of a plurality of different known faults causing the current state of the equipment,

wherein said diagnostic signatures relate the set of known faults which may occur in the equipment to respective fault symptoms which are deemed unrelated to said known faults, and

wherein the system is arranged to calculate the diagnostic data such that a fault symptom being present in said current state symptoms and being deemed indicative of a known fault in said diagnostic signatures provides a more positive contribution to a value indicative of likelihood of the corresponding fault being causative, than a different fault symptom being present in said current state symptoms and being deemed unrelated to the fault in said diagnostic signatures.

2. A fault diagnosis system according to claim 1, wherein the system is connected to receive current state symptoms input by a human operator.

3. A fault diagnosis system according to claim 2, wherein the system is arranged to calculate values indicative of diagnostic rejection power for different possible symptoms to suggest a current state symptom which is to he input by a human operator in order to improve the diagnosis.

4. A fault diagnosis system according to claim 3, wherein the system uses said calculated values indicative of likelihood in calculating said values indicative of diagnostic rejection power.

5. A fault diagnosis system according to claim 1, wherein the system is arranged to store mean time before failure values for equipment components, and wherein the system calculates said values indicative of likelihood using said mean time before failure values.

6. A fault diagnosis system according to claim 5, wherein in a first diagnostic mode said probabilities are calculated using a first relationship with said mean time before failure values and in a second diagnostic mode said probabilities are calculated using a second relationship with said mean time before failure values.

7. A fault diagnosis system according to claim 6, wherein in said second diagnostic mode said values indicative of likelihood are calculated without reference to said mean time before failure values.

8. A fault diagnosis system according to claim 1, wherein the values indicative of likelihood are calculated using a weighting function applied to a set of calculated values to produce the said values indicative of likelihood.

9. A fault diagnosis system according to claim 8, wherein said weighting function is a monotonic function.

10. A fault diagnosis system according to claim 9, wherein said weighting function is an exponential function.

11. A fault diagnosis system according to claim 1, wherein said diagnostic signatures relate the set of known faults which may occur in the equipment to respective fault symptoms which are non-diagnostic in relation to said known faults.

12. A fault diagnosis system according to claim 11, wherein the diagnostic signatures identity a fault symptom to be non-diagnostic in relation to a first known fault, and to be indicative of a second known fault.

13. A fault diagnosis system according to claim 11, wherein the system is arranged to calculate the diagnostic data such that a fault symptom being present in said current state symptoms and being deemed non-diagnostic in relation to a known fault in said diagnostic signatures provides a contribution to a value indicative of likelihood of the corresponding fault being causative, which is substantially equal to a contribution provided to said value by a different fault symptom not being present in said current state symptoms and being deemed non-diagnostic in relation to the fault in said diagnostic signatures.

14. A fault diagnosis system according to claim 1, wherein the system is arranged to calculate the diagnostic data such that a fault symptom, which is deemed indicative of a first number of known faults in said diagnostic signatures, being present in said current state symptoms and being deemed indicative of a known fault in said diagnostic signatures provides a less positive contribution to a value indicative of likelihood of the corresponding fault being causative, than the contribution to the same value provided by a different fault symptom, which is deemed indicative of a second number of known faults in said diagnostic signatures, being present in said current state symptoms and being deemed indicative of the same fault in said diagnostic signatures, wherein said first number of known faults is high compared to said second number of known faults and said second number of known faults is low compared to said first number of known faults.

15. A fault diagnosis system according to claim 14, wherein the system is arranged to calculate the diagnostic data such that a fault symptom being present in said current state symptoms and being deemed indicative of a known fault in said diagnostic signatures, provides a contribution to a value indicative of likelihood for the corresponding fault which is normalized relative to the number of known faults of which the fault symptom is deemed indicative of said diagnostic signatures.

16. A fault diagnosis system according to claim 1, wherein the system is arranged to calculate the diagnostic data such that a fault symptom being present in said current state symptoms and being deemed unrelated to a known fault in said diagnostic signatures provides a cumulative negative contribution to a value indicative of likelihood of the corresponding fault being causative.

17. A fault diagnosis system according to claim 16, wherein the system is arranged to calculate the diagnostic data such that a fault symptom being present in said current state symptoms and being deemed indicative of a known fault in said diagnostic signatures provides a more positive contribution to a value indicative of likelihood of the corresponding fault being causative, than a different fault symptom not being present in said current state symptoms and being deemed unrelated to the fault in said diagnostic signatures.

18. A fault diagnosis system according to claim 1, wherein the system is arranged to calculate the diagnostic data such that a fault symptom, which is deemed unrelated to a first number of known faults in said diagnostic signatures, being present in said current state symptoms and being deemed unrelated to a known fault in said diagnostic signatures provides a less negative contribution to a value indicative of likelihood of the corresponding fault being causative, than the contribution to the same value provided by a different fault symptom, which is deemed unrelated to a second number of known faults in said diagnostic signatures, being present in said current state symptoms and being deemed unrelated to the same fault in said diagnostic signatures, wherein said first number of known faults is high compared to said second number of known faults and said second number of known faults is low compared to said first number of known faults.

19. A fault diagnosis system according to claim 18, wherein the system is arranged to calculate the diagnostic data such that a fault symptom being present in said current state symptoms and being deemed unrelated to a known fault in said diagnostic signatures, provides a contribution to a value indicative of likelihood for the corresponding fault which is normalized relative to the number of known faults of which the fault symptom is deemed unrelated said diagnostic signatures.

20. A fault diagnosis system according to claim 1, wherein the system is arranged to calculate the diagnostic data such that a fault symptom being present in said current state symptoms and being deemed indicative of a known fault in said diagnostic signatures provides a cumulative positive contribution to a value indicative of likelihood of the corresponding fault being causative.

21. A fault diagnosis system according to claim 1, wherein the system is arranged to calculate the diagnostic data such that a fault symptom being present in said current state symptoms and being deemed indicative of a known fault in said diagnostic signatures provides a more positive contribution to a value indicative of likelihood of the corresponding fault being causative, than the fault symptom not being present in said current state symptoms.

22. A fault diagnosis system according to claim 1, wherein the system is arranged to calculate values indicative of the probabilities of different possible fault fixes to be performed by a human operator curing a fault.

23. A fault diagnosis system according to claim 1, wherein the system is arranged to provide different diagnostic modes in which said probabilities are calculated using different algorithmic methods.

24. A fault diagnosis system according to claim 1, wherein the system is arranged to calculate sets of diagnostic data in relation to sets of fault symptoms identifying current states of the system in iterative steps using continually improved knowledge of the current state of the system at each step.

25. A fault diagnosis system according to claim 1, wherein similar symptoms are associated for ease of diagnosis.

26. A fault diagnosis system for diagnosing faults in complex equipment, the system including:

means for storing a set of diagnostic signatures which relates a set of known faults which may occur in the equipment to respective fault symptoms which are deemed indicative of said known faults; and

means for processing said diagnostic signatures and a set of fault symptoms identified for a current state of the equipment, to calculate diagnostic data for identifying a fault causing the current state of the equipment, the diagnostic data including a plurality of values which are indicative of different relative non-zero likelihoods of each of a plurality of different known faults causing the current state of the equipment,

wherein the values indicative of non-zero likelihood are calculated using normalization across a calculated set of values.

27. A fault diagnosis system according to claim 26, wherein the diagnostic signatures of said faults having the smallest likelihoods of being causative are omitted from said recalculation.

28. A fault diagnosis system for diagnosing faults in complex equipment the system including:

means for storing a set of diagnostic signatures which relates a set of known faults which may occur in the equipment to respective fault symptoms which are deemed indicative of said known faults; and

means for processing said diagnostic signatures and a set of fault symptoms identified for a current state of the equipment, to calculate diagnostic data for identifying a fault causing the current state of the equipment, the diagnostic data including a plurality of values which are indicative of different relative non-zero likelihoods of each of a plurality of different known faults causing the current state of the equipment,

wherein said diagnostic signatures relate the set of known faults which may occur in the equipment to respective fault symptoms which are deemed unrelated to said known faults, and

wherein the system is arranged to calculate the diagnostic data such that a fault symptom not being present in said current state symptoms and being deemed indicative of a known fault in said diagnostic signatures provides a more positive contribution to a value indicative of likelihood of the corresponding fault being causative, than a different fault symptom being present in said current state symptoms and being deemed unrelated to the fault in said diagnostic signatures.

29. A fault diagnosis system for diagnosing faults in complex equipment, the system including:

means for storing a set of diagnostic signatures which relates a set of known faults which may occur in the equipment to respective fault symptoms which are deemed indicative of said known faults; and

means for processing said diagnostic signatures and a set of fault symptoms identified for a current state of the equipment, to calculate diagnostic data for identifying a fault causing the current state of the equipment, the diagnostic data including a plurality of values which are indicative of different relative non-zero likelihoods of each of a plurality of different known faults causing the current state of the equipment,

wherein said diagnostic signatures relate the set of known faults which may occur in the equipment to respective fault symptoms which are deemed unrelated to said known faults, and

wherein the system is arranged such that a fault symptom which is deemed unrelated to a known fault has a more positive contribution to a value indicative of likelihood for the fault, when the symptom is not present in said current state symptoms, than the contribution of the same symptom, when present in said current state symptoms, to a value indicative of likelihood for the same fault probability.

30. A fault diagnosis system for diagnosing faults in complex equipment, the system including:

means for storing a set of diagnostic signatures which relates a set of known faults which may occur in the equipment to respective fault symptoms which are deemed indicative of said known faults; and

means for processing said diagnostic signatures and a set of fault symptoms identified for a current state of the equipment, to calculate diagnostic data for identifying a fault causing the current state of the equipment, the diagnostic data including a plurality of values which are indicative of different relative non-zero likelihoods of each of a plurality of different known faults causing the current state of the equipment,

wherein the system is connected to receive an indication of a fault fix input by a human operator and to recalculate said diagnostic data in response thereto.

31. A fault diagnosis system for diagnosing faults in complex equipment, the system including:

means for storing a set of diagnostic signatures which relates a set of known faults which may occur in the equipment to respective fault symptoms which are deemed indicative of said known faults; and

means for processing said diagnostic signatures and a set of fault symptoms identified for a current state of the equipment, to calculate diagnostic data for identifying a fault causing the current state of the equipment, the diagnostic data including a plurality of values which are indicative of different relative non-zero likelihoods of each of a plurality of different known faults causing the current state of the equipment,

wherein said means for processing includes means for calculating the diagnostic data by calculating a first set of values indicative of likelihood, means for identifying faults which have the smallest likelihoods of being causative, and means for performing a recalculation of said diagnostic data whilst taking said faults having the smallest likelihoods of being causative to have an effectively zero likelihood of being causative.

32. A computer readable medium encoded with a computer program to provide a fault diagnosis system for diagnosing faults in complex equipment, the computer program including:

means for storing a set of diagnostic signatures which relates a set of known faults which may occur in the equipment to respective fault symptoms which are deemed indicative of said known faults; and

means for processing said diagnostic signatures and a set of fault symptoms identified for a current state of the equipment, to calculate diagnostic data for identifying a fault causing the current state of the equipment, the diagnostic data including a plurality of values which are indicative of different relative non-zero likelihoods of each of a plurality of different known faults causing the current state of the equipment,

wherein said diagnostic signatures relate the set of known faults which may occur in the equipment to respective fault symptoms which are deemed unrelated to said known faults, and

wherein the system is arranged to calculate the diagnostic data such that a fault symptom being present in said current state symptoms and being deemed indicative of a known fault in said diagnostic signatures provides a more positive contribution to a value indicative of likelihood of the corresponding fault being causative, than a different fault symptom being present in said current state symptoms and being deemed unrelated to the fault in said diagnostic signatures.

33. A computer-implemented method for diagnosing faults in complex equipment, the method comprising:

storing a set of diagnostic signatures which relates a set of known faults which may occur in the equipment to respective fault symptoms which are deemed indicative of said known faults;

processing said diagnostic signatures and a set of fault symptoms identified for a current state of the equipment, to calculate diagnostic data for identifying a fault causing the current state of the equipment, the diagnostic data including a plurality of values which are indicative of different relative non-zero likelihoods of each of a plurality of different known faults causing the current state of the equipment; and

communicating the calculated diagnostic data to a human operator,

wherein the system is connected to receive an indication of a fault fix input by the human operator, and to recalculate said diagnostic data in response thereto.

34. A computer-implemented method for diagnosing faults in complex equipment, the method comprising:

storing a set of diagnostic signatures which relates a set of known faults which may occur in the equipment to respective fault symptoms which are deemed indicative of said known faults;

processing said diagnostic signatures and a set of fault symptoms identified for a current state of the equipment, to calculate diagnostic data for identifying a fault causing the current state of the equipment, the diagnostic data including a plurality of values which are indicative of different relative non-zero likelihoods of each of a plurality of different known faults causing the current state of the equipment wherein the values indicative of non-zero likelihood are calculated using normalization across a calculated set of values; and

storing the calculated diagnostic data.

35. A computer-implemented method for diagnosing faults in complex equipment, the method comprising:

storing a set of diagnostic signatures which relates a set of known faults which may occur in the equipment to respective fault symptoms which are deemed indicative of said known faults;

processing said diagnostic signatures and a set of fault symptoms identified for a current state of the equipment, to calculate diagnostic data for identifying a fault causing the current state of the equipment, the diagnostic data including a plurality of values which are indicative of different relative non-zero likelihoods of each of a plurality of different known faults causing the current state of the equipment,

wherein said processing step includes calculating the diagnostic data by calculating a first set of values indicative of likelihood, identifying faults which have the smallest likelihoods of being causative, and performing a recalculation of said diagnostic data whilst taking said faults having relatively small likelihoods of being causative to have an effectively zero likelihood of being causative; and

storing the calculated diagnostic data.

36. A fault diagnosis system for diagnosing faults in complex equipment, the system including:

means for storing a set of diagnostic signatures which relates a set of known faults which may occur in the equipment to respective fault symptoms which are deemed indicative of said known faults; and

means for processing said diagnostic signatures and a set of fault symptoms identified for a current state of the equipment, to calculate diagnostic data for identifying a fault causing the current state of the equipment, the diagnostic data including a plurality of values which are indicative of different relative non-zero likelihoods of each of a plurality of different known faults causing the current state of the equipment,

wherein the means for storing diagnostic signatures defined three possible states for a fault/symptom pair, namely;

the existence of a link;

the possible existence of a link; and

the certain absence of a link.