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A signal processing toolbox has been realized to enhance the acoustic signal processing of manufactured electronic systems. The toolbox contains a range of signal processing algorithms to help better differentiate the 3D scanned acoustic signals acquired from manufactured parts. The processing has been used to assess the through-life reliability of systems by non-destructively sampling systems during...
The paper deals with the problem of deconvolving sparse ultrasonic NDE traces with time-varying pulses. A sparse dictionary learning algorithm is utilized to learn a time-varying pulse matrix. Each element of the matrix represents an individual pattern of possible local impulse responses. An ultrasonic signal is then decomposed into a sparse representation by the sparse Bayesian learning algorithm...
In this paper, a sparse Bayesian learning-based ultrasonic signal processing method is designed to detect and characterize flaws in thin multilayer structures, where the reflectivity is sparse. Sparse Bayesian learning is first used to decompose an ultrasonic signal into sparse signal representations over an overcomplete dictionary that is learnt from a training data set in advance. Ultrasonic flaw...
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