Abstract: A system and method for measuring various weld characteristics is presented. The system and method can comprise a means to measure penetration depth of butt welds in thin plates, for example, using laser generated ultrasounds. Superimposed line sources (SLS) can be used to generate narrowband ultrasounds. A signal processing procedure that combines wavenumber-frequency (k-?) domain filtering and synthetic phase tuning (SPT) is used to reduce the complexity of Lamb wave signals. The reflection coefficients for different wavelengths corresponding to each wave mode can be calculated. Regression analysis that can include stepwise regression and corrected Akaike's information criterion (AIC) can be performed to build prediction models that use the reflection coefficients as predictors.

Abstract: A system and method for measuring various weld characteristics is presented. The system and method can comprise a means to measure penetration depth of butt welds in thin plates, for example, using laser generated ultrasounds. Superimposed line sources (SLS) can be used to generate narrowband ultrasounds. A signal processing procedure that combines wavenumber-frequency (k-?) domain filtering and synthetic phase tuning (SPT) is used to reduce the complexity of Lamb wave signals. The reflection coefficients for different wavelengths corresponding to each wave mode can be calculated. Regression analysis that can include stepwise regression and corrected Akaike's information criterion (AIC) can be performed to build prediction models that use the reflection coefficients as predictors.

Abstract: A system and method for providing laser generated ultrasound technique utilizing superimposed line sources is presented. The system and method can generate narrowband Lamb waves with a dominant wavelength by superimposing signals of line sources at the pitch corresponding to the desired wavelength. The superposition can be performed in software after data are collected to permit flexibility in the wavelength selected. Selecting the dominant wavelength in signals can reduce signal complexity and the speeds and frequencies of wave modes with the selected wavelength can be determined through dispersion curves. One or more additional techniques including, but not limited to, two-dimensional Fourier transforms and wavelet analysis can be used to further reduce the complexity of the signals. The system and method can be used, for example, for defect detection in thin plates.

Abstract: A method for processing ultrasonic response signals collected from a plurality of measurement locations along a weld of a test sample to determine the presence of defects in the weld may include filtering an ultrasonic response signal from each measurement location to produce a plurality of filtered response signals for each measurement location, wherein each filtered response signal corresponds to specific types of defects. Thereafter, a plurality of energy distributions may be calculated for the weld based on the plurality of filtered response signals for each measurement location. The plurality of energy distributions may be compared to corresponding baseline energy distributions to determine the presence of defects in the weld.

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.

Abstract: A method for determining the type of a defect in a weld may include determining a defect location and a corresponding defect signal by analyzing ultrasonic response signals collected from a plurality of measurement locations along the weld. The defect signal and the plurality of defect proximity signals corresponding to ultrasonic response signals from measurement locations on each side of the defect location may then be input into a trained artificial neural network. The trained artificial neural network may be operable to identify the type of the defect located at the defect location based on the defect signal and the plurality of defect proximity signals and output the type of the defect located at the defect location. The trained artificial neural network may also be operable to determine a defect severity classification based on the defect signal and the plurality of defect proximity signals and output the severity classification.

Abstract: A method for determining the type of a defect in a weld may include determining a defect location and a corresponding defect signal by analyzing ultrasonic response signals collected from a plurality of measurement locations along the weld. The defect signal and the plurality of defect proximity signals corresponding to ultrasonic response signals from measurement locations on each side of the defect location may then be input into a trained artificial neural network. The trained artificial neural network may be operable to identify the type of the defect located at the defect location based on the defect signal and the plurality of defect proximity signals and output the type of the defect located at the defect location. The trained artificial neural network may also be operable to determine a defect severity classification based on the defect signal and the plurality of defect proximity signals and output the severity classification.

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.

Abstract: A method for processing ultrasonic response signals collected from a plurality of measurement locations along a weld of a test sample to determine the presence of defects in the weld may include filtering an ultrasonic response signal from each measurement location to produce a plurality of filtered response signals for each measurement location, wherein each filtered response signal corresponds to specific types of defects. Thereafter, a plurality of energy distributions may be calculated for the weld based on the plurality of filtered response signals for each measurement location. The plurality of energy distributions may be compared to corresponding baseline energy distributions to determine the presence of defects in the weld.