IP Library Granted Patent US 10,909,280
Granted Patent B2
US 10,909,280 · App. 15/334,829 · Granted Feb 2, 2021

Methods and systems for structural health monitoring

Inventors: Lawrence Eric Pado (St. Charles, MO); Jeong-Beom Ihn (Bellevue, WA)
Assignee: The Boeing Company
G06F30/20G01M5/0033G01M5/0066G06N7/005
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Quick Facts
Patent No.
US 10,909,280
App. No.
15/334,829
Granted
Feb 2, 2021
Kind
B2
Abstract

Methods and apparatus for structural health monitoring are described. In one example, a method for use in designing a structural health monitoring (SHM) system for use in monitoring a host structure is described. The method includes one or more of a process for designing SHM systems for any given piece of structural hardware, a process for evaluating a given SHM system, a method to quantify the performance of a given SHM system in comparison to current inspection processes, a finite element modeling approach to determining excitation frequencies to detect damage and for selecting the best time window to use for sensed excitation signals, a Bayesian Network based data fusion technique that fuses in environmental information (load cycles induced on the structure) with a damage index (DI) to produce crack detection and estimation of crack length, and a damage location and sensor selection technique.

Claims (64)

1. A method for use in designing a structural health monitoring (SHM) system, the SHM system including at least one actuator and at least one sensor, said method comprising:

creating a first model of the SHM system using a first finite element method (FEM);

creating a second model of the SHM system using a second FEM, wherein the first model includes structural damage and the second model does not include the structural damage;

simulating signal propagation, from the at least one actuator, and response of the first model and the second model for a first frequency range comprising a plurality of excitation frequencies, wherein, for each excitation frequency of the plurality of excitation frequencies, signal propagation and response of the first model and the second model is simulated for a first period of time, and a plurality of samples of the response of the first model and the second model is collected during the first period of time;

comparing the response of the first model to the response of the second model to determine a difference in the responses at respective frequencies within the first frequency range;

determining, based at least in part on said simulating, a time range within the first period of time during which the simulated response of the SHM system is sensitive to the structural damage;

determining, based at least in part on the comparison, a second frequency range within the first frequency range in which the simulated response of the SHM system is correlatable with the structural damage, wherein the difference in the responses at the respective frequencies within the second frequency range is greater than the difference in the responses at the respective frequencies outside of the second frequency range; and

monitoring, using the SHM system, a host structure for structural damage based on the determined time range and the second frequency range.

2. A method in accordance with claim 1 , the method further comprising:

coupling the at least one actuator and the at least one sensor of the SHM system to an undamaged example of the host structure;

propagating a plurality of signals through the undamaged example of the host structure with the at least one actuator;

collecting responses of the at least one sensor to the plurality of signals; and

characterizing, based at least in part on the collected responses, background noise of the SHM system.

3. A method in accordance with claim 2 , further comprising:

propagating, with the at least one actuator, a plurality of signals through a damaged example of the host structure having at least one crack;

collecting a plurality of waveforms generated by the at least one sensor in response to the plurality of signals;

recording characteristics of the crack; and

associating the collected waveforms with the characteristics of the crack.

4. A method in accordance with claim 3 , further comprising:

determining a damage index for each waveform of a plurality of waveforms of the collected waveforms; and

associating each determined damage index with at least one characteristic of the crack associated with the collected waveform.

5. A method in accordance with claim 4 further comprising analyzing the determined indexes and associated characteristics to determine a probability of detection and a crack characteristic prediction interval.

6. A method accordance with claim 4 , further comprising recording values of an aging factor for the damaged example host, and wherein associating the collected waveforms with the characteristics of the crack comprises associating the collected waveforms with the characteristics of the crack and the values of the aging factor.

7. A method in accordance with claim 6 , further comprising building a Bayesian Network based on the determined damage indexes, the values of the aging factors, and the characteristics of the crack.

8. A method in accordance with claim 7 , further comprising evaluating the Bayesian Network to determine a detection threshold.

9. A method in accordance with claim 1 , wherein the host structure is an aircraft structure.

10. A computer device for use in designing a structural health monitoring (SHM) system, said computer device comprising:

a processor and a memory device in communication with the processor, said processor programmed to:

create a first model of the SHM system using a first finite element model method (FEM);

create a second model of the SHM system using a second FEM, wherein the first model includes structural damage and the second model does not include the structural damage;

simulate signal propagation, emitted from at least one actuator on the first and second models, and response of the first model and the second model for a first frequency range comprising a plurality of excitation frequencies, wherein, for each excitation frequency of the plurality of excitation frequencies, signal propagation and response of the first model and the second model is simulated for a first period of time, and a plurality of samples of the response of the first model and the second model is collected during the first period of time;

compare the response of the first model to the response of the second model to determine a difference in the responses at respective frequencies within the first frequency range;

determine, based at least in part on said simulating, a time range within the first period of time during which the simulated response of the SHM system is sensitive to the structural damage;

determine, based at least in part on the comparison, a second frequency range within the first frequency range in which the simulated response of the SHM system is correlatable with the structural damage, wherein the difference in the responses at the respective frequencies within the second frequency range is greater than the difference in the responses at the respective frequencies outside of the second frequency range; and

monitor, using the SHM system, a host structure for structural damage based on the determined time range and the second frequency range.

11. The computer device in accordance with claim 10 , wherein the processor is further programmed to:

couple the at least one actuator and at least one sensor of the SHM system to an undamaged example of the host structure;

propagate a plurality of signals through the host structure with the at least one actuator;

collect responses of the at least one sensor to the plurality of signals; and

characterize, based at least in part on the collected responses, background noise of the SHM system.

12. The computer device in accordance with claim 11 , wherein the processor is further programmed to:

propagate, with the at least one actuator, a plurality of signals through a damaged example host structure having at least one crack;

collect a plurality of waveforms generated by the at least one sensor in response to the plurality of signals;

record characteristics of the crack; and

associate the collected waveforms with the characteristics of the crack.

13. The computer device in accordance with claim 12 , wherein the processor is further programmed to:

determine a damage index for each waveform of a plurality of waveforms of the collected waveforms; and

associate each determined damage index with at least one characteristic of the crack associated with the collected waveform.

14. The computer device in accordance with claim 13 , wherein the processor is further programmed to analyze the determined damage indexes and the associated characteristics to determine a probability of detection and a crack characteristic prediction interval.

15. The computer device in accordance with claim 13 , wherein the processor is further programmed to:

record values of an aging factor for the damaged example host; and

associate the collected waveforms with the characteristics of the crack and the values of the aging factor.

16. The computer device in accordance with claim 15 , wherein the processor is further programmed to build a Bayesian Network based on the determined damage indexes, the values of the aging factors, and the characteristics of the crack.

17. The computer device in accordance with claim 16 , wherein the processor is further programmed to evaluate the Bayesian Network to determine a detection threshold.

18. The computer device in accordance with claim 10 , wherein the host structure is an aircraft structure.

19. At least one non-transitory computer-readable storage media having computer-executable instructions embodied thereon, wherein when executed by a computing device having at least one processor coupled to at least one memory device, the computer-executable instructions cause the processor to:

create a first model of a structural health monitoring (SHM) system using a first finite element method (FEM);

create a second model of the SHM system using a second FEM, wherein the first model includes structural damage and the second model does not include the structural damage;

simulate signal propagation, emitted from at least one actuator on the first and second models, and response of the first model and the second model for a first frequency range comprising a plurality of excitation frequencies, wherein, for each excitation frequency of the plurality of excitation frequencies, signal propagation and response of the first model and the second model is simulated for a first period of time, and a plurality of samples of the response of the first model and the second model is collected during the first period of time;

comparing the response of the first model to the response of the second model to determine a difference in the responses at respective frequencies within the first frequency range;

determine, based at least in part on said simulating, a time range within the first period of time during which the simulated response of the SHM system is sensitive to the structural damage;

determine, based at least in part on the comparison, a second frequency range within the first frequency range in which the simulated response of the SHM system is correlatable with the structural damage, wherein the difference in the responses at the respective frequencies within the second frequency range is greater than the difference in the responses at the respective frequencies outside of the second frequency range; and

monitor, using the SHM system, a host structure for structural damage based on the determined time range and the second frequency range.

20. The at least one non-transitory computer-readable storage media in accordance with claim 19 , wherein the host structure is an aircraft structure.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 26, 2016
From: PADO, LAWRENCE ERIC; IHN, JEONG-BEOM
To: THE BOEING COMPANY
Reel/Frame 040140/0894 →
Continuity (2)
Division 13647935 · Oct 9, 2012
Related Publication 20170046462A1 · Feb 16, 2017
Cited By (2)
US 12,644,864 US 12,705,721