METHOD FOR INTEGRATING MODELS OF A VEHICLE HEALTH MANAGEMENT SYSTEM

• US 20130116996A1
• Filed: 01/31/2012
• Published: 05/09/2013
• Est. Priority Date: 11/08/2011
• Status: Abandoned Application

• Current Assignee: GE Aviation Systems Limited (GE Aerospace)
• Original Assignee: GE Aviation Systems Limited (GE Aerospace)
• Inventors: Callan, Robert Edward
• Application Number:
  US13/362,666
• Publication Number:
  US 20130116996A1
• Time in Patent Office: Days
• US Class Current: 703/8
• CPC Class Codes: G06F 11/3055 Monitoring arrangements for monitoring the status of the computing system or of the computing system component, e.g. monitoring if the computing system is on, off, available, not available error or fault processing without redundancy G06F11/0703; error detection or correction by redundancy in data representation G06F11/08; error detection or correction by redundancy in operation G06F11/14; error detection or correction by redundancy in hardware G06F11/16
• CPC Class Codes: G07C 5/0808 Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005
• CPC Class Codes: G07C 5/085 using electronic data carriers

Abstract

A method for integrating the function models of a health management system for a vehicle where the vehicle has multiple systems connected to a communications network and the multiple systems send at least one of status messages and raw data regarding at least some of the operational data of the multiple systems and making a determination of a health function of the vehicle.

Claims

1. A method for integrating function models of a health management system for a vehicle having multiple systems connected to a communications network and sending at least one of status messages and raw data regarding at least some operational data of the systems, the method comprising:

providing a plurality of health models, where each health model represents a health function of the vehicle, with at least some of the health models having parameters corresponding to at least some of the operation data;

executing the health models to generate health data related to the corresponding health function;

forming a database of the generated health data from the execution of the health models;

forming a mixture model from the database for at least some of the health functions;

generating a probabilistic graphical model (PGM) from the mixture model for the at least some of the health functions; and

making a determination of a health function based on the generated PGM.

2. The method of claim 1 wherein the forming the mixture model comprises learning the mixture model from the database.

3. The method of claim 2 wherein learning the mixture model comprises selecting a subset of data from the database relevant to the health function to be learned.

4. The method of claim 3 wherein learning the mixture model comprises assigning values for each discrete variable in the subset of data.

5. The method of claim 4 wherein learning the mixture model further comprises partitioning the subset of data according to the assigned values for the discrete variables.

6. The method of claim 4 wherein learning the mixture model comprises learning a mixture model for each partition.

7. The method of claim 4 wherein learning the mixture model further comprises selecting the continuous variables from the subset of data.

8. The method of claim 7 wherein learning the mixture model further comprises setting constraints between the continuous variables.

9. The method of claim 8 wherein learning the mixture model further comprises training the mixture model for the subset of data.

10. The method of claim 9 wherein generating the PGM comprises mapping the mixture model from the subset of data to the PGM.

11. The method of claim 1 wherein the mixture model is formed over continuous parameters and discrete parameters from the database that relate to the corresponding health function.

12. The method of claim 11 wherein the PGM is at least partially decoupled from a structure of the corresponding health module.

13. The method of claim 12 wherein the making the determination of the health function comprises at least one of diagnostic determination and a prognostic determination.