Evaluating the health status of a system

• US 20130046714A1
• Filed: 08/16/2011
• Published: 02/21/2013
• Est. Priority Date: 08/16/2011
• Status: Active Grant

• Current Assignee: The Boeing Co.
• Original Assignee: The Boeing Co.
• Inventors: Harris, Patrick Neal
• Granted Patent: US 8,572,009 B2
• Time in Patent Office: Days
• US Class Current: 706/12
• CPC Class Codes: G01H 1/00 Measuring characteristics of vibrations in solids by using direct conduction to the detector G01H9/00, G01H11/00 take precedence
• CPC Class Codes: G01M 13/028 Acoustic or vibration analysis
• CPC Class Codes: G01M 5/0066 by exciting or detecting vibration or acceleration vibration testing of structures G01M7/00
• CPC Class Codes: G01M 7/00 Vibration-testing of structures; Shock-testing of structures G01M9/00 takes precedence
• CPC Class Codes: Y02B 10/30 Wind power

Abstract

A method and apparatus for determining a health of the system. Groups of vibration data are identified for the system. A group of vibration data in the groups of vibration data comprises data for vibrations of the system at different frequencies over time. The groups of vibration data for the system are stored in a number of associative memories in a computer system. The health of the system is identified based on the groups of vibration data in the number of associative memories.

Claims

1. A method for determining a health of a system comprising:

identify groups of vibration data for the system, wherein a group of vibration data in the groups of vibration data comprises data for vibrations of the system at different frequencies over time;

storing the groups of vibration data for the system in a number of associative memories in a computer system; and

identifying the health of the system based on the groups of vibration data in the number of associative memories.

2. The method of claim 1 further comprising:

generating the groups of vibration data for the system using a sensor system.

3. The method of claim 2, wherein the sensor system comprises a number of vibration sensors.

4. The method of claim 1, wherein identifying the health of the system based on the groups of vibration data in the number of associative memories comprises:

identifying the health of the system based on the groups of vibration data in the number of associative memories using an artificial intelligence system.

5. The method of claim 4, wherein the artificial intelligence system is selected from at least one of a cognitive simulation, a knowledge-based system, a neural network, a fuzzy logic system, and a cognitive model.

6. The method of claim 1, wherein the groups of vibration data comprise images of the vibrations of the system.

7. The method of claim 6, wherein an image in the images represents the data for the vibrations using frequency, intensity, and frequency distribution.

8. The method of claim 6 further comprising:

dividing each image in the images into sections.

9. The method of claim 1, wherein identifying the health of the system based on the groups of vibration data in the number of associative memories is performed using a health analyzer and further comprising:

placing a number of groups of baseline vibration data into the number of associative memories; and

training the health analyzer using the number of groups of baseline vibration data.

10. The method of claim 1, wherein the system is an assembly of components.

11. A method for determining a health of a system, the method comprising:

storing spectrographic images of vibrations of the system in a number of associative memories in a computer system; and

identifying the health of the system based on the spectrographic images stored in the number of associative memories.

12. The method of claim 11, wherein identifying the health of the system based on the spectrographic images stored in the number of associative memories comprises:

identifying the health of the system based on groups of vibration data in the number of associative memories using an artificial intelligence system.

13. A health monitoring system comprising:

a number of associative memories configured to store groups of vibration data for a system, wherein a group of vibration data in the groups of vibration data comprises data for vibrations of the system at different frequencies over time; and

a health analyzer configured to identify a health of the system based on the groups of vibration data in the number of associative memories.

14. The health monitoring system of claim 13 further comprising:

a sensor system configured to generate the groups of vibration data for the system.

15. The health monitoring system of claim 14, wherein the sensor system comprises a number of vibration sensors.

16. The health monitoring system of claim 13, wherein the health analyzer comprises an artificial intelligence system selected from at least one of a cognitive simulation, a knowledge-based system, a neural network, a fuzzy logic system, and a cognitive model.

17. The health monitoring system of claim 13, wherein the groups of vibration data comprise images of the vibrations of the system.

18. The health monitoring system of claim 17, wherein an image in the images represents the data for the vibrations using frequency, intensity, and frequency distribution.

19. The health monitoring system of claim 13, wherein the health analyzer is configured to place a number of groups of baseline vibration data into the number of associative memories;

and train the health analyzer using the number of groups of baseline vibration data.

20. The health monitoring system of claim 13, wherein the system is selected from one of an aircraft, a gearbox, an engine, an engine housing, a control surface, a landing gear system, a fuselage, a spacecraft, a wind turbine, a dam, a computer numerical controlled machine, a building, and a bridge.