Identification of layered material properties using wavelet transform of ultrasonic data

Hanshaw, Timothy C.; Hsu, C.S.; Anderson, Michael J.

doi:10.1109/cca.2000.897537

Cited by 3 publications

(1 citation statement)

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“…A strong signal is reflected from the top of the structure and this initiates a series of reverberations in the top metal substrate which mask a reflected return from the adhesive-bottom substrate boundary [6]. The reflected return is of diagnostic importance since its phase inverts if a bottom face void debond is present.…”

Section: Structurementioning

confidence: 99%

Identification of multilayered structure properties using wavelet-fractal dimension of ultrasonic data

Dun

Chen

Wang

et al. 2009

2009 International Conference on Information and Automation

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This paper present a wavelet-fractal dimension approach for extracting feature from ultrasonic non-destructive evaluation (NDE) data of a test multilayer adhesive structure specimen. These features are then used to estimate the specimen's bonded quality. When the multilayer adhesive structure undergo ultrasonic NDE, echo from interior layers often overlap severely, causing information from individual layers to be obscured or lost completely. A new idea, using wavelet as the ruler to define fractal dimension, is proposed in this paper, based on self similarity of knowing essence of things from collectivity to part, from macrocosm to microcosm, in fractal theory and wavelet transform. Wavelet-fractal dimension is defined as the sum of high-frequency values of decomposed signals. The fractal characteristics of ultrasonic data are gotten from this dimension. The extracted features displayed are effective to analyze and identify the bonded properties. It is believed that the features extracted via the method outlined in this paper provide considerable promise in the area of the test of multilayered structure.

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Section: Structurementioning

confidence: 99%