Analyzing events

• US 20050015217A1
• Filed: 05/14/2004
• Published: 01/20/2005
• Est. Priority Date: 11/16/2001
• Status: Abandoned Application

• Current Assignee: ABB AB (ABB Limited)
• Original Assignee: ABB AB (ABB Limited)
• Inventors: Weidl, Galia, Vollmar, Gerhard
• Application Number:
  US10/845,616
• Publication Number:
  US 20050015217A1
• Time in Patent Office: Days
• US Class Current: 702/185
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G05B 23/0216 Human interface functionality, e.g. monitoring system providing help to the user in the selection of tests or in its configuration
• CPC Class Codes: G05B 23/0281 Quantitative, e.g. mathematical distance; Clustering; Neural networks; Statistical analysis

Abstract

An analyzer arrangement for provision of information about a facility by means of root cause analysis. Storage assembly stores a data model that associates with the facility. The data model contains information about possible events, hypotheses for the root causes of the possible events and symptoms for the hypotheses. A processor provides root cause analysis based on the data model. An input inputs additional information for use in root cause analysis. An adaptor modifies the data model based on the additional information.

Claims

1. An analyzer arrangement for provision of information about a facility by means of root cause analysis, comprising:

storage means for storing a data model that associates with the facility, said data model containing information about possible events, hypotheses for the root causes of the possible events and symptoms for the hypotheses;

processor means for root cause analysis based on the data model;

input means for input of additional information for use in root cause analysis; and

adaptation means for modifying the data model based on the additional information.

2. The analyzer arrangement according to claim 1, wherein the processor means is arranged to process a causally oriented data model.

3. The analyzer arrangement according to claim 2, the causally oriented data model comprising a plurality of objects and information associated with conditional probabilities between the objects, the adaptation means being arranged to modify said conditional probabilities.

4. The analyzer arrangement according to claim 3, wherein the conditional probabilities are modified by modifying at least one conditional probability table of the causally oriented data model.

5. The analyzer arrangement according to claim 1, the adaptation means being arranged to modify the structure of the data model.

6. The analyzer arrangement according to claim 2, wherein the processor means processes simultaneously at least two root cause hypotheses.

7. The analyzer arrangement according to claim 6, wherein said at least two root cause hypotheses share at least one common symptom.

8. The analyzer arrangement according to claim 2, wherein in the causally oriented data model a hypothesis object refers to at least one symptom object and said at least one symptom object refers to an event object.

9. The analyzer arrangement according to claim 2, wherein the causally oriented data model is generated based on a structured data model by a translator engine.

10. The analyzer arrangement according to claim 9, wherein the adaptation means is for modifying the structured data model.

11. The analyzer arrangement as claimed in claim 2, wherein the causally oriented data model comprises a Bayesian Network.

12. The analyzer arrangement according to claim 1, wherein the additional information is for adapting the data models in accordance with changes in the facility.

13. The analyzer arrangement according to claim 1, wherein the additional information comprises information about events occurred in association with the facility.

14. The analyzer arrangement according to claim 1, wherein the additional information comprises operator feedback.

15. The analyzer arrangement according to claim 1, wherein the additional information comprises information about new symptoms.

16. The analyzer arrangement according to claim 1, wherein the additional information comprises information about new root cause hypotheses.

17. The analyzer arrangement according to claim 1, wherein the additional information comprises information from a system controlling the facility.

18. The analyzer arrangement according to claim 1, wherein the additional information is provided based on quantitative data associated with failure frequencies and/or failure weightings of variables associated with the facility.

19. The analyzer arrangement according to claim 1, wherein the additional information is provided based on expertise and/or experiences and/or historical data.

20. The analyzer arrangement according to claim 1, wherein the additional information is based on statistical and/or physical and/or process and/or performance models of the facility.

21. The analyzer arrangement according to claim 1, wherein at least a part of the structure of the data model is based on causality relations between variables associated with the facility.

22. The analyzer arrangement according to claim 1, further comprising a classifier for substantially real-time classification of the additional information and symptoms before they are input as evidences into the root cause analysis.

23. The analyzer arrangement according to claim 1, further comprising a user interface for selection of at least one symptom.

24. The analyzer arrangement according to claim 1, wherein the data model is stored as an aspect of an object in a model describing a facility.

25. The analyzer arrangement according to claim 24, wherein the data model can be adapted to better correspond the facility by replacing the aspect containing the data model with an aspect containing an adapted data model.

26. The analyzer arrangement according to claim 1, further comprising a storage means for storing the data model, said storage means being accessible via a data network.

27. The analyzer arrangement according to claim 1, wherein the data model is generated and stored in a central storage entity based on information from a plurality of individual sources.

28. The analyzer arrangement according to claim 1, wherein an item of data associated with the analysis is transmitted via a wireless interface.

29. The analyzer arrangement according to claim 1, further comprising a portable user device provided with a user interface for input of symptoms and/or additional information and/or for displaying of the results of the analysis.

30. The analyzer arrangement according to claim 1, wherein the processor means analyses the data model to simulate possible impacts of an intended action before any real action is performed.

31. A method of analyzing a facility by means of root cause analysis, comprising:

preparing and storing a data model that associates with the facility in storage means, said data model containing information about possible events, hypotheses for the root causes of the possible events and symptoms for the hypotheses;

input of additional information associated with the facility;

modifying the data model based on the additional information; and

analyzing the facility based on the modified data model.

32. The method according to claim 31, further comprising:

transferring data that associates with the facility from a structured data model into a causally oriented data model and complementing the causally oriented data model with information associated with conditional probabilities between at least two objects of the causally oriented data model; and

simultaneous analysis of at least two root cause hypotheses based on the complemented causally oriented data model.

33. The method according to claim 32, wherein the complementing of the causally oriented data model is accomplished adaptively based on updated information regarding the facility to be analyzed.

34. The method according to claim 31, wherein a structured data model is modified based on the additional information.

35. The method according to claim 31, wherein the additional information is input for adapting the data model in accordance with changes in the facility.

36. The method according to claim 31, wherein the additional information comprises at least one of the following:

information about events occurred in association with the facility;

operator feedback;

information about new symptoms;

information about new root cause hypotheses;

information from a system controlling the facility;

information that is based on quantitative data associated with failure frequencies and/or failure weightings of variables associated with the facility;

information that is based on expertise and/or experiences and/or historical data;

information that is based on statistical and/or physical and/or process models of the facility;

information about the causality relations between variables associated with the facility.

37. The method according to claim 31, wherein the data model is updated in response to a predefined event.

38. The method according to claim 31, wherein the analysis is triggered in response to a signal generated by a control system or an operator.

39. The method according to claim 31, further comprising propagation of a set of evidences gathered for the facility through the data model, making conclusions based on the results of the propagation, and updating the model based on the conclusions.

40. The method according to claim 31, further comprising transportation of data associated with the analysis via a data communication network.

41. A computer program product comprising program code means for performing the steps of claim 31 when the program is run on a computer.

42. A movable user device for use in conjunction with a root cause analyzer for analyzing a facility based on a data model that associates with the facility, said data model containing information about possible events, hypotheses for the root causes of the possible events and symptoms for the hypotheses, the movable user device comprising user interface means for input of additional information for modification of said data model.

43. The movable user device according to claim 42, the user interface being also for presenting results of the analysis.

44. The movable user device according to claim 42, further comprising adaptation means for modifying the data model based on the additional information and analyzer means for producing root cause analyses based on the modified data model.

45. The movable user device according to claim 44 being arranged to process in a substantially real-time manner any new symptoms input into the device.

46. The movable user device according to claim 42, wherein the additional information is of predictive character.

47. The movable user device according to claim 42, arranged to display at least one of the following:

an optimal sequence of actions;

an appropriate action to be taken by the user of the device;

probabilities of simulated effects from an intended action.