45 research outputs found
Flaw Characterization by Low Frequency Scattering Measurements
In order to make a fracture mechanical prediction of the remaining lifetime of a part, it is necessary to know the overall size, shape and orientation of the flaws in the part. This paper describes the determination of these flaw characteristics from measurements of the scattering of low frequency (long wavelength) ultrasound from the flaw. Experimental results are excellent
Computer Aided Interpretation of NDE Signals
In order to improve NDE reliability, it is important to recover as much as possible of the useful information in NDE waveforms. An on-line minicomputer is ideally suited to both the collection of data and the performance of sophisticated signal processing tasks. Using a variety of signal processing techniques, including windowing, self-normalization (of transducer properties and far-field diffraction effects), transformations (Fourier magnitude and phase transforms, autocorrelations, cepstra), feature extraction and pattern· recognition, it has been possible to obtain information about very small defects, strength of adhesive bonds and acoustic emissions which are not available by conventional means. Examples of these various capabilities are given
Characterization of Defects in Adhesive Bonds by Adaptive Learning Networks
Broadband ultrasonic pulses reflected from adhesively bonded structures have been used to train adaptive learning networks (ALN) to identify flawed regions of these structures. The goal is to identify four different types of flaws
Characteristics of Acoustic Emission Signals from Composites
Certain characteristics of acoustic emission (AE) signals from graphite-epoxy composite specimens were correlated last year with the mechanical behavior of the materials. Moisture degradation, which reduced the ultimate strength, resulted in a change in the AE amplitude distribution early in the loading history. Also, AE having distinct frequency spectral types tended to occur at or near singularities in the load curve. In order to transform those observations into a viable NDE tool, two things needed to be done: (1) develop a quicker and more objective method for extracting the pertinent correlations from the data, and (2) develop the statistical relationship between the AE characteristics and some mechanical strength parameter such as ultimate strength or remaining lifetime. The approach taken was to use computer pattern recognition techniques to analyze the data. A problem which was faced in this was the huge amount of data that are available in raw form from a single acoustic emission test. To reduce the amount of data, an intermediate feature extraction step was required and several ways of doing this, based on the prior work, were tried. As a result, the previous correlations between the acoustic emission signal characteristics and the mechanical condition of the composite were confirmed on a more objective basis. This now provides a tool for methodically studying and identifying the specific failure modes which occur in composite materials under various conditions
Dependence of the Accuracy of the Born Inversion on Noise and Bandwidth
The Born Inversions are a set of techniques for reconstructing the shape of a flaw based on the scattering of ultrasound from the flaw. One technique is the one-dimensional Born Inversion, which estimates the radius of a flaw in one direction based on one pulse-echo (i.e., backscattering) measurement in that direction. The robustness of this technique with respect to limitations on the available bandwidth and with respect to the presence of noise in the data have been investigated. The Born Inversion requires a bandwidth sufficient to include at least the range 0.5 \u3c ka \u3c 2 to give accurate estimates. The estimates continue to be accurate even when the amount of noise energy is comparable to the amount of flaw signal energy in the measurement
Detection of Flaws Below Curved Surfaces
A measurement model has been developed to describe ultrasonic measurements made with circular piston transducers in parts with flat or cylindrically curved surfaces. The model includes noise terms to describe electrical noise, scatterer noise and echo noise as well as effects of attenuation, diffraction and Fresnel loss. An experimental procedure for calibrating the noise terms of the model was developed. Experimental measurements were made on a set of known flaws located beneath a cylindrically curved surface. The model was verified by using it to correct the experimental measurements to obtain the absolute scattering amplitude of the flaws. For longitudinal wave propagation within the part, the derived scattering amplitudes were consistent with predictions at internal angles of less than 30°. At larger angles, focusing and aberrations caused a lack of agreement; the model needs further refinement in this case. For shear waves, it was found that the frequency for optimum flaw detection in the presence of material noise is lower than that for longitudinal waves; lower frequency measurements are currently in progress. The measurement model was then used to make preliminary predictions of the best experimental measurement technique for the detection of cracks located under cylindrically curved surfaces