METHOD AND APPARATUS FOR MONITORING STRUCTURAL HEALTH

• US 20100161244A1
• Filed: 12/18/2008
• Published: 06/24/2010
• Est. Priority Date: 12/18/2008
• Status: Active Application

• Current Assignee: Sikorsky Aircraft Corporation (Martin Marietta Corporation)
• Original Assignee: Sikorsky Aircraft Corporation (Martin Marietta Corporation)
• Inventors: Zangor, Roxana, Schaff, Jeffery R., Davis, Mark W., Ghoshal, Anindya, Chaudhry, Zaffir A., Yeh, Jimmy Lih-Min
• Application Number:
  US12/337,848
• Publication Number:
  US 20100161244A1
• Time in Patent Office: Days
• US Class Current: 702/35
• CPC Class Codes: B64D 2045/0085 Devices for aircraft health monitoring, e.g. monitoring flutter or vibration
• CPC Class Codes: B64F 5/60 Testing or inspecting aircraft components or systems
• CPC Class Codes: G01N 2291/0258 Structural degradation, e.g. fatigue of composites, ageing of oils
• CPC Class Codes: G01N 2291/106 one or more transducer arrays
• CPC Class Codes: G01N 2291/2694 Wings or other aircraft parts
• CPC Class Codes: G01N 29/043 in the interior, e.g. by shear waves
• CPC Class Codes: G01N 29/14 using acoustic emission techniques echo of particles G01N29/046; measuring mechanical vibrations or acoustic waves in solids in general G01H1/00
• CPC Class Codes: G01N 29/2475 Embedded probes, i.e. probes incorporated in objects to be inspected
• CPC Class Codes: G01N 29/4472 Mathematical theories or simulation
• CPC Class Codes: G01N 3/32 by applying repeated or pulsating forces

Abstract

A method includes performing a first damage prediction with a computational model using at least data from a first multitude of damage sensors on a structure, performing a second damage prediction with the computational model using at least data from a second multitude of load sensors associated with the structure, and selectively performing a damage monitoring action in response to the first damage prediction and the second damage prediction to determine a structural health A system includes a computing device configured to perform a first damage prediction using at least data from a multitude of damage sensors on a structure, a second damage predication using at least data from a multitude of load sensors associated with the structure, so as to selectively perform a damage monitoring action in response to the first damage prediction and the second damage prediction to determine a structural health of the structure.

Claims

1. A method comprising:

performing a first damage prediction with a computational model using at least data from a first multitude of damage sensors mounted to a structure;

performing a second damage prediction with the computational model using at least data from a second multitude of load sensors associated with the structure; and

selectively performing a damage monitoring action in response to the first damage prediction and the second damage prediction to determine a structural health.

2. The method of claim 1, further comprising:

predicting a structural health of the structure in response to the first damage prediction and the second damage prediction, the structural health including at least one of a comparison of a cumulative damage index to a predetermined threshold, a comparison of an estimated crack size to a critical crack size, and a comparison of an experienced number of cycles to a maximum allowable number of cycles

3. The method of claim 1, further comprising:

updating the computational model on a computer using at least the data from the first multitude of load sensors and using the data from the second multitude of damage sensors, wherein the computational model is stored in memory on a computer.

5. The method of claim 1, further comprising:

identifying areas on the structure where damage is likely to occur under operational conditions;

mounting a first quantity of the multitude of local damage sensors to the areas where damage is likely to occur; and

mounting a second quantity of the multitude of global damages sensors to a plurality of locations on the structure, the second quantity greater than the first quantity.

6. The method of claim 1, further comprising:

receiving data from the second multitude of load sensors, the second multitude of load sensors including at least one of physical load sensors mounted to the structure or virtual load sensors associated with the structure.

7. The method of claim 1, wherein said performing a first damage prediction comprises:

processing the data from the first multitude of damage sensors; and

determining if a crack has formed on the structure using the processed data.

8. The method of claim 1, wherein said performing a second damage prediction comprises:

processing the data from the second multitude of load sensors; and

determining if a sensed load sensed by the second multitude of load sensors exceeds a maximum load for the structure.

9. The method of claim 1, wherein said performing a second damage prediction further comprises:

calculating a cumulative damage index in response to a sensed load not which does not exceed a maximum load; and

determining if the cumulative damage index is greater than or equal to a threshold value.

10. The method of claim 9, wherein said calculating a cumulative damage index comprises:

incrementing a cycle count for a stress level in response to identification that the structure experienced oscillations at the stress level;

calculating a ratio of an experienced number of cycles to a predetermined maximum allowable number of cycles for each stress level experienced by the structure; and

calculating a sum of the ratios for each of the stress levels to calculate a cumulative damage index.

11. The method of claim 1, wherein said selectively performing a damage monitoring action includes estimating an initial crack size calculated from data received from the damage sensors and tracking crack growth tracking in response to the initial crack size if the first damage prediction predicts damage and the second damage prediction predicts damage.

12. The method of claim 1, wherein said selectively performing a damage monitoring action includes tracking crack growth and referencing an initial crack size from a damage database if the first damage prediction predicts damage and the second damage prediction does not predict damage.

13. The method of claim 1, wherein said selectively performing a damage monitoring action further comprises:

incrementing a cycle count for a stress level in response to the structure experiencing oscillations at the stress level if the first damage prediction does not detect predict and the second damage prediction predicts damage; and

proportionally decreasing an estimated crack size based on a cumulative damage index if the first damage prediction does not detect predict and the second damage prediction predicts damage.

14. The method of claim 1, wherein said selectively performing a damage monitoring action further comprises:

incrementing a cycle count for a stress level in response to the structure experiencing oscillations at the stress level if the first damage prediction does not predict damage and the second damage prediction does not predict damage.

15. The method of claim 1, further comprising:

performing a first crack size estimate by referencing a damage database in response to the first damage prediction predicting damage.

16. The method of claim 15, further comprising:

performing a second crack size estimate based on data from the multitude of damage sensors in response to the first damage prediction predicting damage.

17. The method of claim 16, further comprising selecting the second crack size estimate as a final crack size estimate if a difference between the first crack size estimate and the second crack size estimate exceeds a threshold.

18. The method of claim 16, further comprising:

selecting an average of the first crack size estimate and the second crack size as a final crack estimate if a difference between the first crack size estimate and the second crack size estimate does not exceed a threshold.

4. The method of claim 4, further comprising:

receiving data from the first multitude of damage sensors, the first multitude of damage sensors including a multitude of local damage sensors applied to the structure and a multitude of global damage sensors applied to the structure; and

merging data from the multitude of local damage sensors and the multitude of global damage sensors to form a damage data set stored in memory in communication with the computer.

19. A system for structural health monitoring, comprising:

a computing device configured to perform a first damage prediction using at least data from a multitude of damage sensors on a structure, a second damage prediction using at least data from a multitude of load sensors associated with the structure, so as to selectively perform a damage monitoring action in response to the first damage prediction and the second damage prediction to determine a structural health of the structure.

20. The system of claim 19, further comprising:

a damage database configured to contain damage information associated with the multitude of damage sensors, wherein the computing device accesses the damage information to perform the first damage prediction; and

a cycle tracking database configured to contain cycle tracking information associated with a quantity of cycles experienced by the structure at a plurality of stress levels, wherein the computing device accesses the cycle tracking information to perform the second damage prediction.