Artificial intelligence software shell for plant operation simulation

• US 5,412,756 A
• Filed: 12/22/1992
• Issued: 05/02/1995
• Est. Priority Date: 12/22/1992
• Status: Expired due to Fees

• Current Assignee: Mitsubishi Denki Kabushiki Kaisha (Mitsubishi Electric Corporation)
• Original Assignee: Mitsubishi Denki Kabushiki Kaisha (Mitsubishi Electric Corporation)
• Inventors: Schultz, Brian A., Lowenfeld, Simon, Thompson, Robert W. Jr., Bauman, Douglas A.
• Primary Examiner(s): Downs, Robert W.
• Application Number:
  US07/995,209
• Time in Patent Office: 861 Days
• Field of Search: 395/53, 395/77, 395/68, 395/50, 395/61
• US Class Current: 706/45
• CPC Class Codes: G06N 5/043 Distributed expert systems; Blackboards

Abstract

An artificial intelligence software shell for plant operation simulation includes a blackboard module including a database having objects representing plant elements and concepts. A rule-based knowledge source module and a case-based knowledge source module, in communication with the blackboard module, operate on specific predefined blackboard objects. A user interface module, in communication with the blackboard module, enables a user to view blackboard status information. A control module, in communication with the blackboard module and the knowledge source modules, receives input data and controls operation of the knowledge source modules in accordance with a predetermined knowledge source priority scheme.

Claims

1. An artificial intelligence software shell for plant operation simulation comprising:

a blackboard module including a database having objects representing plant elements and concepts;

at least one knowledge source module including an artificial intelligence operation scheme, in communication with the blackboard module, operating on specific predefined blackboard objects;

a user interface module, in communication with the blackboard module, enabling a user to view blackboard status information; and

a control module, in communication with the blackboard module and the at least one knowledge source module, receiving input data and controlling operation of the at least one knowledge source module;

wherein the control module includes;

an event detector module, in communication with the user interface module, determining when the at least one knowledge source should execute, the event detector module including a hash table including a data point structure having entries for objects, and at least one expression list, the hash table being defined by a chaining algorithm.

2. A software shell as claimed in claim 1 wherein the control module includes:

an activation/agenda manager module, in communication with the at least one knowledge source module and the event detector module, executing the at least one knowledge source module in accordance with a predetermined knowledge source priority scheme.

3. A software shell as claimed in claim 2 wherein the at least one knowledge source module includes:

a rule-based knowledge source module having a forward-chaining belief propagation scheme including rules in if-then-else form with associated levels of belief; and

a case-based knowledge source module having a data comparison scheme including predefined patterns and conditions, whereupon execution of the case-based knowledge source, the conditions are inferred to be true if a certain level of closeness is found between received data and the patterns.

4. A software shell as claimed in claim 3 wherein the at least one knowledge source module includes a plurality of knowledge sources of varying priority.

5. A software shell as claimed in claim 3 wherein each of said modules includes a Unix process.

6. A software shell as claimed in claim 3 wherein the blackboard module database includes a hierarchy of objects having vertical hierarchical connections and horizontal links.

7. A software shell as claimed in claim 6 wherein each blackboard object has attributes and each attribute has at least one value, the database including a hash table and plurality of pointers for linking the objects and corresponding attributes and values.

8. A software shell as claimed in claim 6 wherein the vertical hierarchical connections include IS-A and PART-OF hierarchical connections.

9. A software shell as claimed in claim 3 further including message queues and stream sockets for interprocess communication links between modules, messages being communicated in the form of a request-response pair.

10. A software shell as claimed in claim 9 wherein the communication links include data-oriented and control-oriented communication links.

11. A software shell as claimed in claim 10 wherein the data-oriented communication links carry messages including:

an acknowledgment message;

a notification of failure message;

a request for data message;

a data supplied message; and

a knowledge source list message.

12. A software shell as claimed in claim 11 wherein the control-oriented communication links carry messages including:

a start message;

a stop message;

an activate process message;

a set parameters message;

an acknowledgment message; and

a notification of failure message.

13. A software shell as claimed in claim 10 wherein the control-oriented communication links carry messages including:

a start message;

a stop message;

an activate process message;

a set parameters message;

an acknowledgment message; and

a notification of failure message.

14. A software shell as claimed in claim 2 wherein the activation/agenda manager module includes a mechanism for interrupting execution of a knowledge source and executing a higher priority knowledge source in accordance with the knowledge source priority scheme.

15. A software shell as claimed in claim 14 wherein the activation/agenda manager module includes a mechanism for determining whether an interrupted knowledge source should be rescheduled for execution.

16. A software shell as claimed in claim 2 wherein the event detector module includes a mechanism receiving blackboard input data and determining when knowledge source execution preconditions are met.

17. A software shell as claimed in claim 1 wherein the at least one knowledge source module includes:

a rule-based knowledge source module having a forward-chaining belief propagation scheme including rules in if-then-else form with associated levels of belief; and

a case-based knowledge source module having a data comparison scheme including predefined patterns and conditions, whereupon execution of the case-based knowledge source, the conditions are inferred to be true if a certain level of closeness is found between received data and the patterns.

18. A software shell as claimed in claim 17 further including:

a blackboard structure description file including object names and attribute/value pairs for each object;

a rule-based description file including rules forming the rule-based knowledge source and a description of execution preconditions for the rule-based knowledge source; and

a case-based description file including cases forming the case-based knowledge source and a description of execution preconditions for the case-based knowledge source;

wherein the blackboard structure description file, rule-based description file, case-based description file, and input data file are user created.

19. A software shell as claimed in claim 18 further including:

a diagnostics file, created by the shell for each input data file cycle completed, including diagnoses made by the rule-based knowledge source and case matches found by the case-based knowledge source; and

a blackboard status file, created by the shell, including blackboard information as modified by any knowledge sources after completion of each input data file cycle.

20. A software shell as claimed in claim 1 wherein the blackboard module database includes a hierarchy of objects having vertical hierarchical connections and horizontal links.

21. A software shell as claimed in claim 20 wherein each blackboard object has attributes and each attribute has at least one value, the database including a hash table and plurality of pointers for linking the objects and corresponding attributes and values.

22. A software shell as claimed in claim 20 wherein the vertical hierarchical connections include IS-A and PART-OF hierarchical connections.

23. An artificial intelligence software shell for plant operation simulation comprising:

means for storing objects representing plant elements and concepts;

at least one knowledge source module including and artificial intelligence operation scheme, in communication with the means for storing, operating on specific predefined objects;

means, in communication the means for storing, for enabling a user to view object status information; and

means, in communication the means for storing and the at least one knowledge source module, for receiving input data and controlling operation of the at least one knowledge source module;

wherein the means for receiving and controlling include means, in communication with the means for enabling, for determining when the at least one knowledge source module should execute, the means for determining including a hash table including a data point structure having entries for objects, and at least one expression list, the hash table being defined by a chaining algorithm.

24. A software shell as claimed in claim 23 wherein the means for receiving and controlling include:

means, in communication with the at least one knowledge source module and the means for determining, for executing the at least one knowledge source module in accordance with a predetermined knowledge source priority scheme.

25. A software shell as claimed in claim 24 wherein the at least one knowledge source module includes:

a rule-based knowledge source module having a forward-chaining belief propagation scheme including rules in if-then-else form with associated levels of belief; and

a case-based knowledge source module having a data comparison scheme including predefined patterns and conditions, whereupon execution of the case-based knowledge source, the conditions are inferred to be true if a certain level of closeness is found between received data and the patterns.

26. A software shell as claimed in claim 25 wherein the at least one knowledge source module includes a plurality of knowledge sources of varying priority.

27. A software shell as claimed in claim 25 wherein the means for storing includes a database having a hierarchy of objects having vertical hierarchical connections and horizontal links.

28. A software shell as claimed in claim 27 wherein each object has attributes and each attribute has at least one value, the database including a hash table and a plurality of pointers for linking objects and corresponding attributes and values.

29. A software shell as claimed in claim 28 wherein the vertical hierarchical connections include IS-A and PART-OF hierarchical connections.

30. A software shell as claimed in claim 25 wherein the means for executing includes means for interrupting execution of a lower priority knowledge source and executing a higher priority knowledge source in accordance with the knowledge source priority scheme.

31. A software shell as claimed in claim 25 wherein the means for determining includes means for receiving input data and determining when knowledge source execution preconditions are met.

32. A software shell as claimed in claim 25 further including:

a blackboard structure description file including object names and attribute/value pairs for each object;

a rule-based description file including rules forming the rule-based knowledge source and a description of execution preconditions for the rule-based knowledge source;

a case-based description file including cases forming the case-based knowledge source and a description of execution preconditions for the case-based knowledge source;

wherein the blackboard structure description file, rule-based description file, case-based description file, and input data file are user created.

33. A software shell as claimed in claim 32 further including:

a diagnostics file, created by the shell for each input data file cycle completed, including diagnoses made by the rule-based knowledge source and case matches found by the case-based knowledge source; and

a blackboard status file, created by the shell, including blackboard information as modified by any knowledge sources after completion of each input data file cycle.

34. A software shell as claimed in claim 25 further including message queues and stream sockets for interprocess communication links, the messages being communicated in the form of a request-response pair.

35. A software shell as claimed in claim 34 wherein the communication links include data-oriented and control-oriented communication links.

36. A software shell as claimed in claim 35 wherein the data-oriented communication links carry messages including:

an acknowledgment message;

a notification of failure message;

a request for data message;

a data supplied message; and

a knowledge source list message.

37. A software shell as claimed in claim 36 wherein the control-oriented communication links carry messages including:

a start message;

a stop message;

an activate process message;

a set parameters message;

an acknowledgment message; and

a notification of failure message.

38. A method of simulating plant operation with an artificial intelligence software shell comprising the steps of:

storing, in a database, objects representing plant elements and concepts;

reading input data from an input data file;

determining when artificial intelligence knowledge sources should execute in accordance with a predetermined knowledge source priority scheme; and

executing knowledge sources, in accordance with the determination, on specific predefined objects;

wherein the step of determining includes the step of accessing a hash table being defined by a chaining algorithm, the hash table including a data point structure having entries for objects and at least one expression list.

39. A method as claimed in claim 38 wherein the step of executing knowledge sources includes the step of updating object values.

40. A method as claimed in claim 38 wherein the step of executing knowledge sources includes the steps of:

executing rule-based knowledge sources having a forward-chaining belief propagation scheme including rules in if-then-else form with associated levels of belief;

and executing case-based knowledge sources having a data comparison scheme including predefined patterns and conditions.

41. A method as claimed in claim 40 wherein the step of executing case-based knowledge sources includes the step of inferring to be true the conditions if a certain level of closeness is found between received data and the patterns.

42. A method as claimed in claim 40 further including the steps of:

generating a blackboard structure description file including object names and attribute/value pairs for each object;

generating a rule-based description file including rules forming the rule-based knowledge source and execution preconditions; and

generating a case-based description file including cases and a description of execution preconditions.

43. A method as claimed in claim 42 further including the steps of:

generating a rule-based knowledge source module from the rule-based description file; and

generating a case-based knowledge source module from the case-based description file.

44. A method as claimed in claim 40 further including the steps of:

generating a diagnostics file including diagnoses made by the rule-based knowledge sources and case matches found by the case-based knowledge sources; and

generating a blackboard status file including blackboard information as modified by any knowledge sources during execution.

45. A method as claimed in claim 40 wherein the step of executing knowledge sources further includes the step of executing a plurality of knowledge sources having various levels of priority.

46. A method as claimed in claim 38 wherein the step of storing includes the step of storing objects, attributes and values, each object having an attribute and each attribute having at least one value.

47. A method as claimed in claim 46 wherein the step of storing further includes the step of setting up a database including a hash table and a plurality of pointers linking each object with corresponding attributes and values.

48. A method as claimed in claim 47 wherein the step of setting up a database includes the step of creating hierarchical links between objects.

49. A method as claimed in claim 38 wherein the step of executing knowledge sources includes the step of interrupting execution of a lower priority knowledge source and executing a higher priority knowledge source in accordance with the knowledge source priority scheme.

50. A method as claimed in claim 49 wherein the step of executing knowledge sources further includes the step of, after the step of interrupting, determining whether an interrupted knowledge source should be rescheduled for execution.

51. A method as claimed in claim 50 wherein the step of executing knowledge sources further includes the step of, after determining whether an interrupted knowledge source should be rescheduled for execution, rescheduling that knowledge source in accordance with the determination.

52. A method as claimed in claim 38 wherein the step of determining includes the step of determining when knowledge source execution preconditions are met.

53. A method as claimed in claim 38 further including the steps of communicating messages through sockets between modules in the form of request-response pairs.

54. An artificial intelligence software shell for plant operation simulation comprising:

a blackboard module including a database having objects representing plant elements and concepts;

at least one knowledge source module including an artificial intelligence operation scheme, in communication with the blackboard module, operating on specific predefined blackboard objects;

an input data module, in communication with the blackboard module and the at least one knowledge source module, enabling data to be inputted to the shell; and

a control module, in communication with the input data module and the at least one knowledge source module, receiving all input data and controlling operation of the at least one knowledge source in accordance with a predetermined knowledge source interruptibility/priority scheme, the control module includes a hash table defined by a chaining algorithm, the hash table further including a data point structure having entries for objects and at least one expression list.

55. An event detector module for an artificial intelligence software shell for plant operation simulation, the shell including a blackboard module database having objects representing plant elements and concepts, and at least one knowledge source module including an artificial intelligence operation scheme for execution on the blackboard objects, the event detector module comprising:

a communication module receiving input data; and

a determination module, including a hash table defined by a chaining algorithm, for determining when the at least one knowledge source module should execute, the hash table further including a data point structure having entries for objects and at least one expression list.