Methods for monitoring structural health conditions

• US 7,286,964 B2
• Filed: 09/16/2004
• Issued: 10/23/2007
• 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): Wachsman; Hal
• Assistant Examiner(s): O MALLEY, MARY CATHERINE
• Application Number:
  US10/942,714
• Publication Number:
  US 20050075846A1
• Time in Patent Office: 1,132 Days
• Field of Search: 702183-185, 702/188, 73579-582, 735/87, 340/870.11, 340/870.15, 340/3.1, 340 33- 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

Methods and recordable media for monitoring structural health conditions. The present invention provides a method for interrogating a damage of a host structure using a diagnostic network patch (DNP) system having patches. An interrogation module partitions the plurality of patched in subgroups and measures the sensor signals generated and received by actuator and sensor patches, respectively. Then, a process module loads sensor signal data to identify Lamb wave modes, determine the time of arrival of the modes and generate a tomographic image. It also determines distribution of other structural condition indices to generate tomographic images of the host structure. A set of tomographic images can be stacked to generate a hyperspectral tomography cube. A classification module generates codebook based on K-mean/Learning Vector Quantization algorithm and uses a neural-fuzzy-inference system to determine the type of damages of the host structure.

Claims

1. A computer-implemented method for interrogating health conditions of a structure using a plurality of diagnostic network patches (DNP) implemented thereto, each of the patches being able to operate as at least one of a transmitter patch and a sensor patch, the method comprising:

forming a diagnostic network including the patches and a plurality of signal transmission paths, each said signal transmission path being a signal link between a transmitter patch and a sensor patch;

representing the diagnostic network by a graph, wherein the patches and signal transmission paths are respectively abstracted as nodes and edges in the graph;

partitioning the diagnostic network into one or more subgroups, each of the subgroups including a designated transmitter patch and one or more sensor patches;

causing, by use of a computer processor, the designated transmitter patch to transmit a signal and the sensor patches to receive the signal;

comparing the received signal with a baseline signal to determine a deviation therebetween, the baseline signal being measured by use of the diagnostic network in absence of structural anomaly; and

analyzing the deviation to determine the health conditions of the structure.

2. The method of claim 1, further comprising:

storing the received signal and the deviation in a depository.

3. The method of claim 1, wherein the step of analyzing includes:

performing diagnostic data processing;

generating a structural condition index; and

generating a tomographic image.

4. The method of claim 1, wherein the anomaly includes at least one selected from the group consisting of damage, impact, cavity, corrosion, local change of internal temperature and pressure, degradation of material, and a repair bonding patch applied to the structure.

5. The method of claim 1, wherein two neighboring subgroups share one or more patches.

6. The method claim 1, wherein the step of representing the diagnostic network by a graph includes:

generating a topological architecture, x, of the diagnostic network, wherein x is represented by the equation;

x={x₁₂, x₁₃, . . . , x<sub>n−

1, n</sub>}

and wherein x_ij ε

{0,1} is a decision variable representing the path between i^th and j^th nodes and n is the number of the nodes.

7. The method of claim 1, wherein the step of representing the diagnostic network by a graph includes:

performing a common integer programming formulation to generate a matrix of path connection, each element (i,k) of the matrix being 1 if i^th sensor patch is connected to k^th transmitter patch and 0 otherwise.

8. The method of claim 1, further comprising:

optimizing the diagnostic network by use of a cost variable associated with network path uniformity so that network performance is maximized while the number of patches is minimized.

9. The method of claim 8, wherein the cost variable is the distance of signal transmission, the number of intersection points of each said signal transmission path crossed by neighboring paths or a sensitivity of each said signal transmission path to an excitation frequency of the signal.

10. The method of claim 1, further comprising, prior to the step of forming a diagnostic network:

applying one or more artificial defects to the structure to simulate damages in the structure, wherein the step of forming a diagnostic network is performed by a genetic algorithm to optimize the diagnostic network.

11. The method of claim 1, wherein the step of causing the designated transmitter patch to transmit a signal and the sensor patches to receive the signal includes:

providing a toneburst signal for the designated transmitter patch, the toneburst signal having a spectral energy distribution within a narrow frequency bandwidth centered at one excitation frequency.

12. The method of claim 1, further comprising:

repeating the steps of forming a diagnostic network to comparing the received signal at a plurality of excitation frequencies of the signal.

13. The method of claim 1, wherein the signal is a Lamb wave signal or a vibrational signal.

14. The method of claim 1, further comprising:

storing coordinates of patches and setup information including an excitation frequency of the signal, types of patches, identification numbers of patches, a voltage level of patches, and operational status of patches.

15. The method of claim 1, further comprising:

converting the baseline signal and received signal into eXtensible Markup Language (XML) formatted data.

16. A computer readable medium carrying one or more sequences of instructions for interrogating health conditions of a structure using a plurality of diagnostic network patches (DNP) implemented thereto, each of the patches being able to operate as at least one of a transmitter patch and a sensor patch, 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:

forming a diagnostic network including the patches and a plurality of signal transmission paths, each said signal transmission path being a signal link between a transmitter patch and a sensor patch;

representing the diagnostic network by a graph, wherein the patches and signal transmission paths are respectively abstracted as nodes and edges in the graph;

partitioning the diagnostic network into one or more subgroups, each of the subgroups including a designated transmitter patch and one or more sensor patches;

causing the designated transmitter patch to transmit a signal and the sensor patches to receive the signal;

comparing the received signal with a baseline signal to determine a deviation therebetween, the baseline signal being measured by use of the diagnostic network in absence of structural anomaly; and

analyzing the deviation to determine the health conditions of the structure.

17. The computer readable medium of claim 16, wherein execution of one or more sequences of instructions by one or more processors causes the one or more processors to perform the additional step of storing the received signal and the deviation in a depository.

18. The computer readable medium of claim 16, wherein the step of analyzing includes:

performing diagnostic data processing;

generating a structural condition index; and

generating a tomographic image.

19. The computer readable medium of claim 16, wherein two neighboring subgroups share one or more patches.

20. The computer readable medium of claim 16, wherein the step of representing the diagnostic network by a graph includes:

generating a topological architecture, x, of the diagnostic network, wherein x is represented by the equation;

x={x₁₂, x₁₃, . . . , x<sub>n−

1, n</sub>}

and wherein x_ij ε

{0,1} is a decision variable representing the path between i^th and j^th nodes and n is the number of the nodes.

21. The computer readable medium of claim 16, wherein the step of representing the diagnostic network by a graph includes:

performing a common integer programming formulation to generate a matrix of path connection, each element (i,k) of the matrix being 1 if i^th sensor patch is connected to k^th transmitter patch and 0 otherwise.

22. The computer readable medium of claim 16, wherein execution of one or more sequences of instructions by one or more processors causes the one or more processors to perform the additional step of optimizing the diagnostic network by use of a cost variable associated with network path uniformity so that network performance is maximized while the number of patches is minimized.

23. The computer readable medium of claim 22, wherein the cost variable is the distance of signal transmission, the number of intersection points of each said signal transmission path crossed by neighboring paths or a sensitivity of each said signal transmission path to an excitation frequency of the signal.

24. The computer readable medium of claim 16, wherein execution of one or more sequences of instructions by one or more processors causes the one or more processors to perform the additional step of, prior to the step of forming a diagnostic network:

applying one or more artificial defects to the structure to simulate damages in the structure, wherein the step of forming a diagnostic network is performed by a genetic algorithm to optimize the diagnostic network.

25. The computer readable medium of claim 16, wherein execution of one or more sequences of instructions by one or more processors causes the one or more processors to perform the additional step of repeating the steps of forming a diagnostic network to comparing the received signal at a plurality of excitation frequencies of the signal.

26. The computer readable medium of claim 16, wherein execution of one or more sequences of instructions by one or more processors causes the one or more processors to perform the additional step of:

storing coordinates of patches and setup information including an excitation frequency of the signal, types of patches, identification numbers of patches, a voltage level of patches, and operational status of patches.

27. The method of claim 16, wherein execution of one or more sequences of instructions by one or more processors causes the one or more processors to perform the additional step of converting the baseline signal and received signal into eXtensible Markup Language (XML) formatted data.

28. The computer readable medium of claim 16, wherein the one or more sequences of instructions implement a remote processing method of Simple Object Access Protocol (SOAP) or Remote Procedure Call/eXtensible Markup Language (RPC-XML) for Internet Web Services.