Provision of process related information

• US 20040250166A1
• Filed: 05/28/2004
• Published: 12/09/2004
• Est. Priority Date: 06/05/2001
• Status: Active Grant

• Current Assignee: ABB Schweiz AG (ABB Limited)
• Original Assignee: ABB AB (ABB Limited)
• Inventors: Dahlquist, Erik, Weidl, Galia
• Granted Patent: US 7,213,174 B2
• Time in Patent Office: Days
• US Class Current: 714/37
• CPC Class Codes: G05B 23/0278 Qualitative, e.g. if-then rules; Fuzzy logic; Lookup tables; Symptomatic search; FMEA

Abstract

A method and an analyser for producing information associated with a process is disclosed. In the method information from information sources that associate with the process is processed to classify said information into characteristic states. Results of said classification are then analysed for producing information associated with at least one root cause for an event by means of at least one analysing technology that is capable of reasoning under at least one uncertainty.

Claims

1. A method of producing information associated with a process, the method comprising:

processing information from information sources that associate with the process to classify said information into characteristic states; and

analyzing the results of said classification for producing information associated with a root cause for an event by means of at least one analyzing technology that is capable of reasoning under at least one uncertainty.

2. The method as claimed in claim 1, wherein the event comprises an abnormal condition.

3. The method as claimed in claim 2, wherein the event comprises a failure.

4. The method as claimed in claim 1, wherein the classification reduces the number of variable states that are input into the analyzing stage.

5. The method as claimed in claim 1, wherein information comprising numeric variables is classified into characteristic states based on the value of the variables.

6. The method as claimed in claim 5, wherein a value is classified into a characteristic state that defines a range of values said value belongs to.

7. The method as claimed in claim 1, further comprising determining a trend for information from a source and classifying the information based on the determined trend.

8. The method as claimed in claim 1, wherein the classification comprises mapping of time series of sampled signal points into time series of signal states.

9. The method as claimed in claim 1, wherein at least one characteristic state is expressed by means of a binary value.

10. The method as claimed in claim 9, wherein information input into the analyzing stage comprises a string of binary values.

11. The method as claimed in claim 1, wherein information input into the analyzing stage comprises a continuous distribution of variables.

12. The method as claimed in claim 1, wherein at least one characteristic state indicates a condition.

13. The method as claimed in claim 1, wherein an alarm signal is classified between real and false states.

14. The method as claimed in claim 1, wherein alarm signals are classified into root cause alarms and effect alarms, and only root cause alarms are presented to a user.

15. The method as claimed in claim 1, wherein said processing further comprises predicting development and/or trend of an information signal.

16. The method as claimed in claim 1, wherein information from information sources is processed adaptively.

17. The method as claimed in claim 1, comprising use of structured information associated with the process.

18. The method as claimed in claim 17, wherein at least a part of the structured information is acquired by means of lower level diagnostic packages.

19. The method as claimed in claim 17, wherein said structured information comprises at least one model describing the process.

20. The method as claimed in claim 19, wherein a model describes physics of the process.

21. The method as claimed in claim 19, wherein a model describes mathematical characteristics of the process.

22. The method as claimed in claim 19, wherein a model is based on statistical information or experience from the process.

23. The method as claimed in claim 1, comprising training of the information processing stage based on information about at least one trend or development determined for the process.

24. The method as claimed in claim 1, comprising use of at least one neural network for said processing of information prior the results of said processing are input into the analyzing stage.

25. The method as claimed in claim 24, wherein at least one neuro-fuzzy network is used.

26. The method as claimed in claim 1, comprising use of principal component analysis and/or artificial intelligence agents.

27. The method as claimed in claim 1, wherein said capability to reason under at least one uncertainty is provided by adaptive root cause analysis.

28. The method as claimed in claim 27, wherein a hybrid combination of at least two different adaptive root cause analysis methods is used for the reasoning under at least one uncertainty.

29. The method as claimed in claim 27, wherein the adaptive root cause analysis is provided by means of at least one of the following methods:

Bayesian inference;

neuro-fuzzy inference;

case based reasoning.

30. The method as claimed in claim 29, wherein the cased based reasoning is for identifying an abnormality, the Bayesian inference is for determination of at least one root cause behind the abnormality, and the neuro-fuzzy inference is for analyzing abnormalities between stages and/or phase transitions in the process.

31. The method as claimed in claim 1, comprising comparing of simulated or computed data with data obtained from the process.

32. The method as claimed in claim 31, comprising trending a deviation determined by said comparing.

33. The method as claimed in claim 1, comprising normalization of information on which the analysis is to be based on.

34. The method as claimed in claim 1, further comprising a step of testing for fault and/or abnormality patterns after said classification.

35. The method as claimed in claim 1, further comprising monitoring for development of a root cause for an event.

36. The method as claimed in claim 1, wherein at least a part of the information for the analysis is provided by a distributed control system.

37. The method as claimed in claim 1, wherein the output of the analyzing stage is used in real-time control of the process.

38. The method as claimed in claim 1, comprising prediction of required actions based on the output of the analyzing stage.

39. The method as claimed in claim 37, wherein control actions are ranked based on at least one of the following list:

probabilities;

membership grade;

minimal error measure of similarity.

40. The method as claimed in claim 1, wherein information associated with a plurality of root causes is produced, and said root causes are ranked based on the probabilities thereof.

41. The method as claimed in claim 1, wherein a part of the analysis is carried out by a data processing facility in a location which is remote with respect to the physical location of at least one part of the process.

42. The method as claimed in claim 1, wherein an operator may input feedback after presentation of the results of the analysis, and updated results are provided based on the feedback.

56. A computer program product comprising program code means for performing any of steps of claim 1 when the program is run on a computer.

43. An analyzer for analyzing a process, the analyzer comprising processing means for classifying information associated with the process into characteristic states and analyzer means for producing information associated with a root cause of an event by analyzing information from the processing means, the analyzer means being capable of reasoning under at least one uncertainty.

44. The analyzer as claimed in claim 43, further comprising prediction means for predicting development and/or trend of an information signal.

45. The analyzer as claimed in claim 43, wherein the processing means and/or the prediction means are implemented by means of at least one neural network.

46. The analyzer as claimed in claim 45, further comprising at least one neuro-fuzzy network.

47. The analyzer as claimed in claim 43, further comprising a storage means for storing structured information associated with the process.

48. The analyzer as claimed in claim 47, wherein the structured information comprises at least one model describing the process and/or the physics of the process.

49. The analyzer as claimed in claim 43, wherein the analyzer means comprises means for implementing adaptive root cause analysis.

50. The analyzer as claimed in claim 49, wherein the analyser means comprises means for hybrid implementation of at least two different root cause analysis methods.

51. The analyzer as claimed in claim 43, further comprising graphical user interface.

52. Use of an analyzer for provision of information associated with a root cause of an event, said analyzer being constructed in accordance with claim 43.

53. The process control system comprising an analyzer as claimed in claim 43.

54. The process control system as claimed in claim 53, further comprising means for communicating a message to a remote operator, said means being based on a communication media that is based on use of Internet protocol and/or a wireless communication protocol.

55. The process control system as claimed in claim 53, further comprising at least one database for storing information associated with components, spare parts and similar, and an association between the analyzer and said at least one database.

57. A user interface for an operator of a process comprising display means for displaying at least one root cause for an event in a process, said at least one root cause being estimated by processing information from information sources that associate with the process to classify said information into characteristic states and analyzing the results of said classification for producing information associated with said at least one root cause by means of at least one analyzing technology that is capable of reasoning under at least one uncertainty.

58. The user interface as claimed in claim 57, wherein the display means are adapted to provide a visual indication of the most probable root cause of an event.

59. A data transmission signal for transmission of data associated with a process, wherein the data transmission signals includes data associated with at least one root cause for an event in the process, said data being estimated by processing information from information sources that associate with the process to classify said information into characteristic states and analyzing the results of said classification for producing information associated with said at least one root cause by means of at least one analyzing technology that is capable of reasoning under at least one uncertainty.