Systems and methods of generating diagnostic images for structural health monitoring

• US 7,584,075 B2
• Filed: 07/10/2007
• Issued: 09/01/2009
• Est. Priority Date: 09/22/2003
• Status: Expired due to Fees

• Current Assignee: Advanced Structure Monitoring, Inc.
• Original Assignee: Advanced Structure Monitoring, Inc.
• Inventors: Kim, Hyeung-Yun
• Primary Examiner(s): Feliciano; Eliseo Ramos
• Assistant Examiner(s): O MALLEY, MARY CATHERINE
• Application Number:
  US11/827,319
• Publication Number:
  US 20070265806A1
• Time in Patent Office: 784 Days
• Field of Search: 702 33- 40, 702/81, 702182-183, 702/185, 702/188, 703/1, 703 6- 7, 714 25- 26, 714 47- 48, 340/870.11, 340/870.15, 340/3.1, 340/3.3, 340 331- 332
• US Class Current: 702/183
• CPC Class Codes: G01H 11/00 Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by detecting changes in electric or magnetic properties
• CPC Class Codes: G01H 11/08 using piezoelectric devices
• CPC Class Codes: G01H 9/004 using fibre optic sensors light guides per se G02B6/00, acousto-optical devices specially adapted for gating or modulating in optical wave guides G02F1/125
• CPC Class Codes: G01M 11/086 Details about the embedment of the optical fiber within the DUT
• CPC Class Codes: G01M 5/0033 by determining damage, crack or wear
• CPC Class Codes: G01M 5/0066 by exciting or detecting vibration or acceleration vibration testing of structures G01M7/00
• CPC Class Codes: G01M 5/0091 by using electromagnetic excitation or detection
• CPC Class Codes: G01N 2291/011 Velocity or travel time
• CPC Class Codes: G01N 2291/015 Attenuation, scattering
• CPC Class Codes: G01N 2291/02491 Materials with nonlinear acoustic properties
• CPC Class Codes: G01N 2291/0258 Structural degradation, e.g. fatigue of composites, ageing of oils
• CPC Class Codes: G01N 2291/0422 Shear waves, transverse waves, horizontally polarised waves
• CPC Class Codes: G01N 2291/0423 Surface waves, e.g. Rayleigh waves, Love waves
• CPC Class Codes: G01N 2291/0427 Flexural waves, plate waves, e.g. Lamb waves, tuning fork, cantilever
• CPC Class Codes: G01N 2291/106 one or more transducer arrays
• CPC Class Codes: G01N 29/043 in the interior, e.g. by shear waves
• CPC Class Codes: G01N 29/0609 Display arrangements, e.g. colour displays indicating or recording in connection with measuring in general G01D
• CPC Class Codes: G01N 29/0672 by acoustic tomography medical tomography A61B8/13
• CPC Class Codes: G01N 29/07 by measuring propagation velocity or propagation time of acoustic waves
• CPC Class Codes: G01N 29/223 Supports, positioning or alignment in fixed situation mounting transducers per se G10K11/004
• CPC Class Codes: G01N 29/245 : Ceramic probes, e.g. lead zirconate titanate [PZT] probes
• CPC Class Codes: G01N 29/2475 : Embedded probes, i.e. probes incorporated in objects to be inspected
• CPC Class Codes: G01N 29/2493 : Wheel shaped probes
• CPC Class Codes: G01N 29/28 : providing acoustic coupling , e.g. water impedance matching G10K11/02
• CPC Class Codes: G01N 29/4418 : with a model, e.g. best-fit, regression analysis
• CPC Class Codes: G01N 29/4463 : Signal correction, e.g. distance amplitude correction [DAC], distance gain size [DGS], noise filtering

Abstract

Systems, methods and recordable media for generating tomographic images to monitor structural health conditions. A method includes the steps of obtaining a plurality of damage index values for a network that is coupled to a host structure and has a plurality of diagnostic network patches (DNP), generating a distribution of damage index value over a surface using the obtained damage index values, and formatting the distribution as at least one tomographic image. Each of the patches is able to operate as at least one of a transmitter patch and a sensor patch. The damage index values is a quantity to be affected by damage in the host structure or associated with signals generated by the patches in a response to an impact on the host structure.

Claims

1. A computer-implemented method of generating a tomographic image for structural health monitoring, comprising:

obtaining one or more damage index values for a network coupled to a structure and having a plurality of diagnostic network patches (DNP) secured to the structure, each of the patches being able to operate as at least one of a transmitter patch for transmitting a signal that propagates in the structure and a sensor patch for sensing the signal, each of the damage index values being a quantity to be affected by damage in a host structure of the network;

generating a distribution of damage index value over a surface using the obtained damage index values; and

formatting, by use of a computer process, the distribution as at least one tomographic image.

2. The method of claim 1, wherein the step of generating a distribution includes:

designating a plurality of points on the surface; and

assigning damage index values to the designated points using the obtained damage index values.

3. The method of claim 2, wherein the step of assigning damage index values includes:

employing an expert system to determine damage index values at the designated points.

4. The method of claim 3, wherein the expert system is a neuro-fuzzy inference system based on a fuzzy if-then rule for a distance of each of the transmission paths of the network and collaborated with a neural network.

5. The method of claim 4, wherein the neural network is a back propagation multiplayer perception with radial basis function networks.

6. The method of claim 2, wherein the step of generating a distribution further includes:

generating mesh-grid points on the surface; and

determining damage index values at the mesh-grid points using the assigned damage index values.

7. The method of claim 6, wherein the step of determining damage index values at the mesh-grid points includes:

utilizing an interpolation method to calculate damage index values at the mesh-grid points.

8. The method of claim 6, wherein the step of generating mesh-grid points on the surface includes:

performing Delaunay triangulation to form the mesh-grid points.

9. The method of claim 6, wherein the step of determining damage index values at the mesh-grid points includes:

applying an algebraic reconstruction technique.

10. The method of claim 6, wherein the step of determining damage index values at the mesh-grid points includes:

applying a simultaneous iterative reconstruction technique (SIRT).

11. The method of claim 6, wherein the step of determining damage index values at the mesh-grid points includes:

applying a scatter-operator-eigenfunction based technique.

12. The method of claim 6, further comprising:

training a cooperative hybrid expert system with an artificial damage; and

utilizing the cooperative hybrid expert system to filter out a false hot-spot region in the distribution.

13. The method of claim 6, further comprising:

refining the damage index values at the mesh-grid points; and

utilizing a genetic algorithm to assign the refined damage index values to the mesh-grid points thereby to generate an updated distribution of damage index value.

14. The method of claim 6, further comprising:

converting data of the mesh-grid points and the damage index values at the mesh-grid points into an eXtensible Markup Language (XML) formatted document.

15. The method of claim 1, wherein the step of generating a distribution includes:

determining intersection points where signal transmission paths of the network cross each other; and

for each said intersection point, assigning a product of two damage index values respectively associated with two crossing signal transmission paths to said intersection point.

16. The method of claim 15, wherein the step of generating a distribution further includes:

determining bisection points of a portion of the signal transmission paths, wherein each of the portion of signal transmission paths does not cross other signal transmission path, and

for each said bisection point, assigning a damage index value associated with a corresponding path to said bisection point.

17. The method of claim 15, wherein the product of two damage index values is calculated by use of a three-dimensional Gaussian function.

18. The method of claim 1, further comprising:

storing the tomographic image in a depository.

19. The method of claim 1, further comprising:

repeating the steps of obtaining a plurality of damage index values to formatting the distribution at a plurality of excitation frequencies thereby to generate a plurality of tomographic images; and

stacking the tomographic images to generate a hyperspectral cube.

20. The method of claim 1, further comprising:

repeating the steps of obtaining a plurality of damage index values to formatting the distribution at a plurality of consecutive temporal points of a damage state thereby to generate a plurality of tomographic images; and

stacking the tomographic images to generate a damage evolution manifold, wherein said damage evolution manifold represents an evolved state of a structural condition of the host structure.

21. A computer-implemented method of generating a tomographic image for structural health monitoring, comprising:

obtaining one or more damage index values for a network coupled to a structure and having a plurality of diagnostic network patches (DNP) secured to the structure, each of the patches being able to operate as at least one of a transmitter patch for transmitting a signal that propagates in the structure and a sensor patch for sensing the signal, each of the damage index values being associated with a signal generated by one of the patches in response to an impact on a host structure of the network;

generating a distribution of damage index value over a surface using the obtained damage index values; and

formatting, by use of a computer process, the distribution as at least one tomographic image.

22. The method of claim 21, wherein the step of generating a distribution includes:

designating a plurality of points on the surface; and

assigning damage index values to the designated points using the obtained damage index values.

23. The method of claim 22, wherein the step of generating a distribution further includes:

generating mesh-grid points on the surface; and

determining damage index values at the mesh-grid points using the assigned damage index values.

24. A computer readable medium carrying one or more sequences of instructions for generating a tomographic image for structural health monitoring, wherein execution of one or more sequences of instructions by one or more processors causes the one or more processors to perform the steps of:

obtaining one or more damage index values for a network coupled to a structure and having a plurality of diagnostic network patches (DNP) secured to the structure, each of the patches being able to operate as at least one of a transmitter patch for transmitting a signal that propagates in the structure and a sensor patch for sensing the signal, each of the damage index values being a quantity to be affected by damage in a host structure of the network;

generating a distribution of damage index value over a surface using the obtained damage index values; and

formatting, by use of a computer process, the distribution as at least one tomographic image.

25. The computer readable medium of claim 24, wherein the step of generating a distribution includes:

designating a plurality of points on the surface; and

assigning damage index values to the designated points using the obtained damage index values.

26. The computer readable medium of claim 25, wherein the step of generating a distribution further includes:

generating mesh-grid points on the surface; and

determining damage index values at the mesh-grid points using the assigned damage index values.

27. The computer readable medium of claim 24, wherein the step of generating a distribution includes:

determining intersection points where signal transmission paths of the network cross each other; and

for each said intersection point, assigning a product of two damage index values respectively associated with two crossing signal transmission paths to said intersection point.

28. The computer readable medium of claim 27, wherein the step of generating a distribution further includes:

determining bisection points of a portion of the signal transmission paths, wherein each of the portion of signal transmission paths does not cross other signal transmission path, and

for each said bisection point, assigning a damage index value associated with a corresponding path to said bisection point.

29. The computer readable medium of claim 24, wherein execution of one or more sequences of instructions by one or more processors causes the one or more processors to perform the additional steps of:

repeating the steps of obtaining a plurality of damage index values to formatting the distribution at a plurality of excitation frequencies thereby to generate a plurality of tomographic images; and

stacking the tomographic images to generate a hyperspectral cube.

30. The computer readable medium of claim 24, wherein execution of one or more sequences of instructions by one or more processors causes the one or more processors to perform the additional steps of:

repeating the steps of obtaining a plurality of damage index values to formatting the distribution at a plurality of consecutive temporal points of a damage state thereby to generate a plurality of tomographic images; and

stacking the tomographic images to generate a damage evolution manifold, wherein said damage evolution manifold represents an evolved state of a structural condition of the host structure.

31. The computer readable medium of claim 24, wherein the one or more sequences of instructions implement a wireless communication method of Wireless Application Protocol (WAP) or Wireless Markup Language (WML) for the Internet Web Access of a WAP-enabled cell phone, a Pocket PC with a HTML browser, or an HTML-enabled device.

32. A computer readable medium carrying one or more sequences of instructions for generating a tomographic image for structural health monitoring, wherein execution of one or more sequences of instructions by one or more processors causes the one or more processors to perform the steps of:

obtaining one or more damage index values for a network coupled to a structure and having a plurality of diagnostic network patches (DNP) secured to the structure, each of the patches being able to operate as at least one of a transmitter patch for transmitting a signal that propagates in the structure and a sensor patch for sensing the signal, each of the damage index values being associated with a signal generated by one of the patches in response to an impact on a host structure of the network;

generating a distribution of damage index value over a surface using the obtained damage index values; and

formatting, by use of a computer process, the distribution as at least one tomographic image.

33. The computer readable medium of claim 32, wherein the step of generating a distribution includes:

designating a plurality of points on the surface; and

assigning damage index values to the designated points using the obtained damage index values.

34. The computer readable medium of claim 33, wherein the step of generating a distribution further includes:

generating mesh-grid points on the surface; and

determining damage index values at the mesh-grid points using the assigned damage index values.

35. The computer readable medium of claim 32, wherein execution of one or more sequences of instructions by one or more processors causes the one or more processors to perform the additional steps of:

repeating the steps of obtaining a plurality of damage index values to formatting the distribution at a plurality of excitation frequencies thereby to generate a plurality of tomographic images; and

stacking the tomographic images to generate a hyperspectral cube.

36. The computer readable medium of claim 32, wherein execution of one or more sequences of instructions by one or more processors causes the one or more processors to perform the additional steps of:

repeating the steps of obtaining a plurality of damage index values to formatting the distribution at a plurality of consecutive temporal points of a damage state thereby to generate a plurality of tomographic images; and

stacking the tomographic images to generate a damage evolution manifold, wherein said damage evolution manifold represents an evolved state of a structural condition of the host structure.

37. A system for generating a tomographic image for structural health monitoring, comprising:

a network to be coupled to a host structure and having a plurality of diagnostic network patches (DNP) secured to the structure, each of the patches being able to operate as at least one of a transmitter patch for transmitting a signal that propagates in the structure and a sensor patch for sensing the signal;

means for obtaining a plurality of damage index values for the network;

means for generating a distribution of damage index value over a surface using the obtained damage index values; and

means for formatting, by use of a computer process, the distribution as at least one tomographic image.

38. The system of claim 37, wherein the means for generating a distribution includes:

means for designating a plurality of points on the surface; and

means for assigning damage index values to the designated points using the obtained damage index values.

39. The system of claim 37, wherein the means for generating a distribution further. includes:

means for generating mesh-grid points on the surface; and

means for determining damage index values at the mesh-grid points using the assigned damage index values.

40. The system of claim 37, wherein the means for generating a distribution includes:

means for determining intersection points where signal transmission paths of the network cross each other; and

means for assigning, for each said intersection point, a product of two damage index values respectively associated with two crossing signal transmission paths to said intersection point.

41. The system of claim 40. wherein the means for generating a distribution further includes:

means for determining bisection points of a portion of the signal transmission paths, wherein each of the portion of signal transmission paths does not cross other signal transmission path, and

means for assigning, for each said bisection point, a damage index value associated with a corresponding path to said bisection point.

42. The system of claim 37, further comprising:

means for operating the means for obtaining a plurality of damage index values, for generating a distribution of damage index values, and for formatting the distribution at a plurality of excitation frequencies thereby to generate a plurality of tomographic images; and

means for stacking the tomographic images to generate a hyperspectral cube.

43. The system of claim 37, further comprising

means for operating the means for obtaining a plurality of damage index values, for generating a distribution of damage index values, and for formatting the distribution at a plurality of consecutive temporal points of a damage state thereby to generate a plurality of tomographic images;

and

means for stacking the tomographic images to generate a damage evolution manifold, wherein said damage evolution manifold represents an evolved state of a structural condition of the host structure.