Application of Wavelet Analysis in Two-Dimensional Ultrasonic Flaw Detection

Anjani R. Achanta, Vittal Rao

Research output: Contribution to journalConference article

1 Scopus citations

Abstract

Ultrasonic inspection uses sound waves of short wavelength and high frequency to detect flaws in materials. The pulse of ultrasonic energy that is reflected by a discontinuity such as a void, delamination, inclusion or any other type of imperfection is highlighted as flaw in the ultrasonic image. Usually an ultrasonic signal that is reflected from the material contains multiple interfering microstructure echoes, with random amplitudes and phases. The interference noise produced by the unresolvable scatterers is randomly distributed throughout the material, thus reducing the diagnostic value of the ultrasonic images. In the process of developing structural health monitoring techniques for locating damage in composite patches bonded to aluminum panels, a two-dimensional flaw detection technique is proposed to improve the signal-to-noise ratio in the ultrasonic B-scan image. Wavelet Packet Transforms are used for decomposing the signal to obtain maximum detail information about the flaws. Once the input signal (B-scan image) is split into different frequency channels, a selection of useful information about flaw is done based upon the statistics of the detail images. An adaptive thresholding procedure is employed to extract the flaw information from the selected detail images. The method has been verified with reasonable accuracy in predicting disbonds in composite patch repairs of aging airframes. The advantage of this method is that it gives the flaw location that is easier to interpret with less ambiguity. The amount of data being processed is less thus reducing the complexity of processing. The method proved successful in locating the delaminations along the length and width of the composite patch. The procedure has also been applied to detect damage in multiple locations.

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