Interactive, constraint-network prognostics and diagnostics to control errors and conflicts (IPDN)

• US 10,496,463 B2
• Filed: 09/11/2017
• Issued: 12/03/2019
• Est. Priority Date: 06/30/2010
• Status: Active Grant

• Current Assignee: Purdue Research Foundation (Purdue University)
• Original Assignee: Purdue Research Foundation (Purdue University)
• Inventors: Chen, Xin W., Nof, Shimon Y.
• Primary Examiner(s): Maskulinski, Michael
• Application Number:
  US15/700,917
• Publication Number:
  US 20180089006A1
• Time in Patent Office: 813 Days
• CPC Class Codes: G05B 23/0251 Abstraction hierarchy, e.g. "complex systems", i.e. system is divided in subsystems, subsystems are monitored and results are combined to decide on status of whole system
• CPC Class Codes: G06F 11/0709 in a distributed system consisting of a plurality of standalone computer nodes, e.g. clusters, client-server systems
• CPC Class Codes: G06F 11/076 by exceeding a count or rate limit, e.g. word- or bit count limit
• CPC Class Codes: G06F 11/079 Root cause analysis, i.e. error or fault diagnosis in a hardware test environment G06F11/22; in a software test environment G06F11/36
• CPC Class Codes: G06F 11/3676 for coverage analysis

Abstract

Methods for interactively preventing and detecting conflicts and errors (CEs) through prognostics and diagnostics. Centralized and Decentralized Conflict and Error Prevention and Detection (CEPD) Logic is developed for prognostics and diagnostics over three types of real-world constraint networks: random networks (RN), scale-free networks (SFN), and Bose-Einstein condensation networks (BECN). A method is provided for selecting an appropriate CEPD algorithm from a plurality of algorithms having either centralized or decentralized CEPD logic, based on analysis of the characteristics of the CEPD algorithms and the characteristics of the constraint network.

Claims

1. A system, comprising:

two or more cooperative units, wherein the two or more cooperative units periodically exhibit conflicts and errors

at least one control unit configured to;

receive a list of parameters associated with the cooperative units and interactions between the cooperative units by at least one control unit;

perform conflict and error detection, including;

a) providing a list of at least two constraints, each constraint defining a task to be accomplished or a requirement to be satisfied by one or more cooperative units by a first time;

b) identifying one or more constraints from the list, which need to be satisfied by a defined time;

c) identifying for each identified constraint whether any conflict or error exists;

where a conflict occurs whenever an inconsistency between two or more cooperative units occurs, and an error is associated with any condition that is inconsistent with the list of parameters;

d) marking the constraints for which an error or conflict has been identified;

e) incrementing a mark count for each cooperative unit associated with each marked constraint;

perform at least one of diagnosis and prognosis based at least in part on the marked constraints; and

wherein the at least one control unit is further configured to;

create and update at least one constraint (C) table using the list of parameters associated with the cooperative units and interactions between the cooperative units;

use the constraint table in step e) to identify each cooperative unit associated with each constraint marked in step d);

model dependencies between constraints to form at least one relationship (R) table using the C table and the list of parameters associated with a system of cooperative units and interactions between the cooperative units;

use the at least one R table in performing the at least one of diagnosis and prognosis in the at least one control unit;

establish and update a constraint network encompassing the constraints and their dependencies using the C and R tables, wherein each node in the constraint network is represented by a constraint and links between nodes represent relationships between constraints;

diagnose and mark constraints that have conflicts or errors through the analysis of the constraint network; and

predict and mark constraints that have or will have conflicts or errors through the analysis of the constraint network.

2. The system of claim 1, wherein the at least one control unit is further configured to perform diagnosis, including:

f) identifying each constraint having a first predefined relationship with each constraint marked in d); and

g) marking the constraints identified in f).

3. The system of claim 2, wherein the predetermined relationship includes a condition wherein a time associated with the identified constraint is the same or earlier than a time associated with the constraint marked in step d).

4. The system of claim 2, wherein the predetermined relationship includes a condition wherein a time associated with the identified constraint is later than a time associated with the constraint marked in step d).

5. The system of claim 3, wherein the at least control unit is further configured to perform prognosis, including:

h) identifying each constraint having a second predefined relationship with each constraint marked in d); and

i) marking the constraints identified in h).

6. The system of claim 1, wherein the at least one control unit is further configured to mark in a different manner the constraints for which an error or conflict has not been identified.

7. The system of claim 1, wherein the at least one control unit is further configured to cause visualization of steps a), b) and c) and enable interactions between users based at least in part on using Petri nets or other state transition graphs.

8. A system for preventing and detecting conflicts and errors through prognostics and diagnostics, comprising:

multiple autonomous agents or control units;

each receiving a list of parameters associated with agents or control units with which the current agent or control unit has an inclusive, mutually exclusive, or other relationship, each modeling a first constraint;

each performing detection, including;

a) identifying any conflict or error associated with the first constraint;

b) marking the first constraint to identify whether any conflict or error is identified;

c) communicating a message to another of the agents or control units, the message including information determined at least in part based on whether any conflict or error is identified; and

wherein,

step a) further comprises, if information from another of the agents and control units identifies that no conflict exists, then identifying a second constraint associated with the first constraint; and

step b) further comprises marking the first constraint to indicate no conflict or error identified.

9. The system of claim 8, wherein step c) further comprises communicating the message to an agent or control unit associated with the second constraint.

10. The system of claim 9, further comprising:

d) identifying a third constraint associated with the first constraint; and

e) communicating a second message to an agent or control unit associated with the third constraint.

11. The system of claim 10, wherein the second message comprises information identifying whether a conflict or error was identified.

12. The system of claim 9, wherein the message comprises information identifying whether a conflict or error was identified.

13. The system of claim 12, further comprising:

d) identifying a third constraint associated with the first constraint; and

e) communicating a second message to an agent or control unit associated with the third constraint.

14. The system of claim 13, wherein the second message comprises information identifying whether a conflict or error was identified.