Methods and systems for detecting defects in welded structures utilizing pattern matching

• US 8,256,296 B2
• Filed: 08/03/2009
• Issued: 09/04/2012
• Est. Priority Date: 08/03/2009
• Status: Active Grant

• Current Assignee: Georgia Tech Research Corporation (University System of Georgia)
• Original Assignee: Georgia Tech Research Corporation (University System of Georgia)
• Inventors: Ume, Ifeanyi Charles, Li, Renfu, Rogge, Matthew, Wu, Tsun-Yen
• Primary Examiner(s): Kwok, Helen C.
• Application Number:
  US12/534,296
• Publication Number:
  US 20110023609A1
• Time in Patent Office: 1,128 Days
• Field of Search: 73596-600, 736/02, 736/22, 736/27
• US Class Current: 73/627
• CPC Class Codes: G01N 2291/0258 Structural degradation, e.g. fatigue of composites, ageing of oils
• CPC Class Codes: G01N 2291/2675 Seam, butt welding
• CPC Class Codes: G01N 2291/2694 Wings or other aircraft parts
• CPC Class Codes: G01N 29/11 by measuring attenuation of acoustic waves
• CPC Class Codes: G01N 29/449 Statistical methods not provided for in G01N29/4409, e.g. averaging, smoothing and interpolation

Abstract

A method for processing ultrasonic response signals collected from a plurality of measurement locations along a weld to determine the presence of a defect in the weld may include filtering an ultrasonic response signal from each of the measurement locations to produce a filtered response signal for each of the measurement locations. Thereafter, an ultrasonic energy for each of the measurement locations is calculated with the corresponding filtered response signal. The ultrasonic energy for each measurement location is then compared to the ultrasonic energy of adjacent measurement locations to identify potential defect locations. When the ultrasonic energy of a measurement location is less than the ultrasonic energy of the adjacent measurement locations, the measurement location is a potential defect location. The presence of a defect in the weld is then determined by analyzing fluctuations in the ultrasonic energy at measurement locations neighboring the potential defect locations.

Claims

1. A method for determining if a defect is present in a weld from ultrasonic response signals collected from a plurality of measurement locations along a weld, the method comprising:

filtering an ultrasonic response signal from each of the measurement locations to produce a filtered response signal for each of the measurement locations;

calculating an ultrasonic energy for each of the measurement locations with the corresponding filtered response signal;

comparing the ultrasonic energy for each measurement location to the ultrasonic energy of adjacent measurement locations to identify potential defect locations, wherein, when the ultrasonic energy of a measurement location is less than the ultrasonic energy of the adjacent measurement locations, the measurement location is a potential defect location; and

analyzing fluctuations in the ultrasonic energy at measurement locations neighboring the potential defect locations to determine if a defect is present in the weld, wherein fluctuations in the ultrasonic energy are analyzed by comparing the ultrasonic energy of a potential defect location to the ultrasonic energy of a plurality of measurement locations on each side of the potential defect location, wherein, when the ultrasonic energy increases monotonically over the plurality of measurement locations on each side of the potential defect location, the potential defect location comprises a defect.

2. The method of claim 1 wherein the ultrasonic response signal from each of the measurement locations is filtered by:

decomposing the ultrasonic response signal by discrete wavelet transform to produce a set of wavelet coefficients for the ultrasonic response signal;

band-pass filtering the set of wavelet coefficients to isolate a frequency range sensitive to defects in the weld; and

producing the filtered response signal for the measurement location by performing inverse discrete wavelet transform on the corresponding filtered set of wavelet coefficients.

3. The method of claim 1 wherein, when the potential defect location comprises a defect, the ultrasonic energy of the potential defect location and the ultrasonic energy of measurement locations neighboring the potential defect location are compared to defect energy patterns to determine what type of defect is present in the weld.

4. The method of claim 1 wherein fluctuations in the ultrasonic energy are analyzed by comparing the ultrasonic energy of a potential defect location and the ultrasonic energy of measurement locations neighboring the potential defect location to defect energy patterns to determine if the potential defect location comprises a defect.

5. A method for testing a weld for defects, the method comprising:

inducing ultrasonic signals at multiple measurement locations along the weld;

collecting an ultrasonic response signal for each of the measurement locations;

filtering the ultrasonic response signal from each of the measurement locations to produce a filtered response signal for each of the measurement locations;

calculating an ultrasonic energy for each of the measurement locations with the corresponding filtered response signal;

determining an ultrasonic energy distribution for the weld based on the ultrasonic energy for each of the measurement locations;

identifying local minima in the ultrasonic energy distribution; and

analyzing fluctuations in the ultrasonic energy distribution around each local minimum to determine if a defect is present in the weld, wherein fluctuations in the ultrasonic energy distribution around a local minimum are analyzed by comparing the ultrasonic energy of the local minimum to the ultrasonic energy of a plurality of measurement locations on each side of the local minimum, wherein, when the ultrasonic energy distribution increases monotonically at the plurality of measurement locations on each side of the local minimum, the local minimum is a defect location.

6. The method of claim 5 wherein the ultrasonic response signal from each of the measurement locations is filtered by:

decomposing the ultrasonic response signal by discrete wavelet transform to produce a set of wavelet coefficients for the ultrasonic response signal;

band-pass filtering the set of wavelet coefficients to isolate a frequency range sensitive to defects in the weld; and

producing the filtered response signal for a measurement location by performing inverse discrete wavelet transform on the filtered set of wavelet coefficients.

7. The method of claim 5 wherein, when the local minimum is a defect location, the ultrasonic energy of the local minimum and the ultrasonic energy of measurement locations neighboring the local minimum are compared to defect energy patterns to determine what type of defect is present in the weld.

8. The method of claim 5 wherein fluctuations in the ultrasonic energy distribution are analyzed by comparing the ultrasonic energy of a local minimum and the ultrasonic energy of measurement locations neighboring the local minimum to defect energy patterns to determine if a defect is present in the weld at the local minimum.

9. The method of claim 5 wherein the ultrasonic response signal for each measurement location is filtered to isolate a frequency range from about 0.977 MHz to about 1.464 MHz.

10. The method of claim 5 wherein ultrasonic signals are induced by directing an output beam of a pulsed laser source on to a surface of a test sample in which the weld is located.

11. The method of claim 5 wherein:

a plurality of ultrasonic signals are induced in the weld at each of the measurement locations; and

a plurality of ultrasonic response signals are collected at each of the measurement locations and averaged.

12. A defect detection system for identifying defects in a weld, the defect detection system comprising a controller, an acoustic signal generator, an acoustic signal detector, and a positioning device, wherein the acoustic signal generator, the acoustic signal detector and the positioning device are electrically coupled to the controller and the controller is programmed to:

induce ultrasonic signals at multiple measurement locations along the weld with the acoustic signal generator;

collect an ultrasonic response signal from each of the measurement locations with the acoustic signal detector and store each ultrasonic response signal in a memory operatively associated with the controller;

filter the ultrasonic response signal from each of the measurement locations to produce a filtered response signal for the corresponding measurement locations;

calculate an ultrasonic energy for each of the measurement locations with the corresponding filtered response signal;

compare the ultrasonic energy for each measurement location to the ultrasonic energy of adjacent measurement locations to identify potential defect locations, wherein, when the ultrasonic energy of a measurement location is less than the ultrasonic energy of the adjacent measurement locations, the measurement location is a potential defect location; and

analyze fluctuations in the ultrasonic energy at measurement locations neighboring the potential defect locations to determine if a defect is present in the weld, wherein the controller is programmed to analyze fluctuations in the ultrasonic energy by comparing the ultrasonic energy of a potential defect location to the ultrasonic energy of a plurality of measurement locations on each side of the potential defect location, wherein, when the ultrasonic energy increases monotonically over the plurality of measurement locations on each side of the potential defect location, the potential defect location comprises a defect.

13. The defect detection system of claim 12 wherein the controller is programmed to filter the ultrasonic response signal from each of the measurement locations by:

decomposing the ultrasonic response signal by discrete wavelet transform to produce a set of wavelet coefficients for the ultrasonic response signal;

band-pass filtering the set of wavelet coefficients to isolate a frequency range sensitive to defects in the weld; and

producing the filtered response signal for the measurement location by performing inverse discrete wavelet transform on the filtered set of wavelet coefficients.

14. The defect detection system of claim 12 wherein, when the potential defect location comprises a defect, the controller is programmed to compare the ultrasonic energy of the potential defect location and the ultrasonic energy of measurement locations neighboring the potential defect location to defect energy patterns to determine what type of defect is present in the weld.

15. The defect detection system of claim 12 wherein the controller is programmed to analyze fluctuations in the ultrasonic energy by comparing the ultrasonic energy of a potential defect location and the ultrasonic energy of measurement locations neighboring the potential defect location to defect energy patterns to determine if the potential defect location comprises a defect.

16. The defect detection system of claim 12 wherein the acoustic signal generator is a pulsed laser source.

17. The defect detection system of claim 12 wherein the acoustic signal detector is an EMAT sensor.