METHOD FOR CALCULATING CONFIDENCE ON PREDICTION IN FAULT DIAGNOSIS SYSTEMS

• US 20090276136A1
• Filed: 04/30/2008
• Published: 11/05/2009
• Est. Priority Date: 04/30/2008
• Status: Active Grant

• Current Assignee: Rtx Corporation
• Original Assignee: United Technologies Corporation (Raytheon Technologies Corporation d/b/a RTX)
• Inventors: Butler, Steven Wayne
• Granted Patent: US 8,417,432 B2
• Time in Patent Office: Days
• US Class Current: 701/100
• CPC Class Codes: F05B 2260/80 Diagnostics
• CPC Class Codes: G05B 23/0281 Quantitative, e.g. mathematical distance; Clustering; Neural networks; Statistical analysis

Abstract

A method and system is developed that provides a confidence measure of a prediction of a fault in a gas turbine engine. The confidence measure is developed based upon evaluating the results of a plurality of past predictions and comparing them to an actual fault.

Claims

1. A fault diagnosis system comprising:

a fault detection system for taking in a plurality of sensor readings from a gas turbine engine;

said plurality of sensors providing readings to a fault isolation system, and to a network communicating with a database of prior predictions, and the database associating the prior predictions with a confidence level; and

said fault isolation system providing a predicted fault to an output, and a confidence level in the predicted output also being provided to the output.

2. The system as set forth in claim 1, wherein the database is developed, at least in part, using a model-based fault isolation system.

3. The system as set forth in claim 2, wherein a regression network is trained based upon the model-based fault isolation system.

4. The system as set forth in claim 2, wherein the database is also developed based upon actual examples of correct and incorrect predictions.

5. The system as set forth in claim 1, wherein the database is developed based upon actual examples of correct and incorrect predictions.

6. A method of operating a fault prediction system including the steps of:

(a) taking in a plurality of sensor readings from a gas turbine engine;

(b) providing readings to a fault isolation system, and to a network communicating with a database of prior predictions, the database associating the prior predictions with a confidence level; and

(c) said fault isolation system providing a predicted fault to an output, and a confidence level in the predicted fault also being provided to the output.

7. The method as set forth in claim 6, wherein the database is developed, at least in part, using a model-based fault isolation system.

8. The method as set forth in claim 7, wherein a regression network is trained based upon the model-based fault isolation system.

9. The method as set forth in claim 7, wherein the database also is developed utilizing actual examples of correct and incorrect predictions.

10. The method as set forth in claim 6, wherein the database is developed utilizing actual examples of correct and incorrect predictions.