Process and system for automatically constructing a bayes network

• US 20030014229A1
• Filed: 07/10/2002
• Published: 01/16/2003
• Est. Priority Date: 07/10/2001
• Status: Abandoned Application

• Current Assignee: Daimler Chrysler Company LLC (Stellantis NV)
• Original Assignee: Daimler Chrysler Company LLC (Stellantis NV)
• Inventors: Borth, Michael, Von Hasseln, Hermann
• Application Number:
  US10/191,797
• Publication Number:
  US 20030014229A1
• Time in Patent Office: Days
• US Class Current: 703/2
• CPC Class Codes: G05B 23/0254 based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks

Abstract

A process for constructing a Bayes network for the imaging and diagnosis of a technical system by means of a system description includes the following steps: constructing a system input node for each system input of the system; constructing a system output node for each system output of the system; imaging all components of the system by means of component state nodes, component input nodes and component output nodes; constructing linkages between component state nodes of different components by means of direct logical and/or causal relationships between function states of components; constructing linkages between component output nodes and component input nodes of different components by means of flows of material, energy and/or information in the system; constructing linkages between system input nodes and component input nodes by means of flows of material, energy and/or information in the system; and constructing linkages between component output nodes and system output nodes by means of flows of material, energy and/or information in the system.

Claims

1. A process for constructing a Bayes network for imaging and diagnosis of a technical system that is characterized by a system description, said process comprising:

constructing a system input node for each system input of the system;

constructing a system output node for each system output of the system;

imaging all components of the system by means of component state nodes, component input nodes and component output nodes;

constructing linkages between component state nodes of different components by means of direct logical and/or causal relationships between states of components;

constructing linkages between component output nodes and component input nodes of different components by way of flows of material, energy and/or information in the system;

constructing linkages between system input nodes and component input nodes by way of flows of material, energy and/or information in the system; and

constructing linkages between component output nodes and system output nodes by way of flows of material, energy and/or information in the system.

2. The process according to claim 1, wherein the step of constructing a system input node comprises establishing all possible states of the system input in the system input node.

3. The process according to claim 2, wherein an occurrence probability is assigned to each possible state of the system input.

4. The process according to claim 1, wherein the step of constructing the system output node comprises establishing all possible states of the system output in the system output node.

5. The process according to claim 1, wherein the step of imaging the components of the system comprises:

checking whether a component is constructed of partial components; and

if partial components are detected, all partial components are imaged by means of component state nodes, component input nodes and component output nodes.

6. The process according to claim 5, wherein another component state node for an overall function state is added to the imaging of a component that comprises partial components.

7. The process according to claim 1, wherein during imaging of the components:

a component state node is constructed for each component of the system;

a component input node is constructed for each input variable of a component; and

a component output node is constructed for each output variable of a component.

8. The process according to claim 7, wherein the step of establishing a component state node comprises:

establishing all possible function states of a particular component in the component state node; and

assigning an occurrence probability to each function state.

9. The process according to claim 7, wherein the step of establishing a component input node comprises establishing all possible states of input variables in a component input node.

10. The process according to claim 7, wherein the step of establishing a component output node comprises establishing all possible states of the output variables in the component output node.

11. The process according to claim 1, wherein the step of imaging the components of the system comprises constructing linkages within a component between a component input node and a component output node, and between a component state node and a component output node.

12. The process according to claim 11, wherein the step of constructing linkages within a component comprises assigning an occurrence probability to each possible state of a component output node as a function of the states of a linked component input node and a component state node.

13. The process according to claim 1, wherein the step of imaging components of the system comprises inserting network fragments from a component library.

14. The process according to claim 1, wherein the step of constructing linkages between component state nodes of different components comprises:

checking whether a function state of at least one component directly influences the state of another component;

inserting one connection respectively from each influencing component to the influenced component; and

assigning occurrence probabilities to each state of the influenced component as a function of the state of each influencing component.

15. The process according to claim 1, wherein the step of constructing linkages between component output nodes and a component input node of different components comprises assigning an occurrence probability to each state of the component input node, as a function of the state of each linked component output node.

16. The process according to claim 1, wherein the step of constructing linkages between system input nodes and a component input node comprises assigning an occurrence probability to each state of the component input node, as a function of a state of each linked system input node.

17. The process according to claim 1, wherein the step of constructing linkages between component output nodes and a system output node comprises assigning an occurrence probability to each state of the system output node, as a function of a state of each component output node.

19. The system according to claim 18, further comprising a component library for the storage of network fragments, wherein the construction unit can store and output network fragments in the component library.

20. The system according to claim 18, further comprising a setup control unit in which setup rules are filed for network components and network linkages, with the construction unit and the completion unit being able to take setup rules from the setup control unit.

18. A system for constructing a Bayes network for imaging and diagnosis of a technical system that is characterized by a system description, by performing the steps of

constructing a system input node for each system input of the system;

constructing a system output node for each system output of the system;

imaging all components of the system by means of component state nodes, component input nodes and component output nodes;

constructing linkages between component state nodes of different components by means of direct logical and/or causal relationships between states of components;

constructing linkages between component output nodes and component input nodes of different components by way of flows of material, energy and/or information in the system;

constructing linkages between system input nodes and component input nodes by way of flows of material, energy and/or information in the system; and

constructing linkages between component output nodes and system output nodes by way of flows of material, energy and/or information in the system;

the system comprising;

a source unit for storage or editing of the system description;

a component analysis unit for analyzing the system and disassembling it into components;

a construction unit for constructing network fragments assigned to the components; and

a completion unit for assembling the network fragments to form an overall network.