Instantaneous Frequency Estimation of Ultrasonic Testing Signal Based on Matching Pursuits

Du, Xian

doi:10.4028/www.scientific.net/amr.631-632.1367

Cited by 1 publication

(3 citation statements)

References 12 publications

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“…(8) states that the optimal Gabor parameter vector θ q can be estimated by maximizing the correlation between d(θ q ) and the vector e, which is a weighted average of the columns of the residue matrix E q . because (8) fits a single Gabor parameter vector θ q , it can be easily solved using optimization methods such as the chirplet signal decomposition algorithm [9], which have been used in this paper.…”

Section: B Improving the Approximationmentioning

confidence: 99%

“…because (8) fits a single Gabor parameter vector θ q , it can be easily solved using optimization methods such as the chirplet signal decomposition algorithm [9], which have been used in this paper. once θ q is updated by (8), it is kept fixed, and b q is updated by a simple linear least squares minimization [25]:…”

Section: B Improving the Approximationmentioning

confidence: 99%

“…1 In Fig. 4(a) we present the unconstrained approximation of atom 1 obtained by calculating e from (8). because this estimation involves data from all three signals, it obtains much better results and improves the rMsE from 0.025 to 0.015.…”

Section: A a Single Cluster Simulation Examplementioning

confidence: 99%

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Cluster-enhanced sparse approximation of overlapping ultrasonic echoes

Mor

Aladjem

Azoulay

2015

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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Ultrasonic pulse-echo methods have been used extensively in non-destructive testing of layered structures. In acoustic measurements on thin layers, the resulting echoes from two successive interfaces overlap in time, making it difficult to assess the individual echo parameters. Over the last decade sparse approximation methods have been extensively used to address this issue. These methods employ a large dictionary of elementary functions (atoms) and attempt to select the smallest subset of atoms (sparsest approximation) that represent the ultrasonic signal accurately. In this paper we propose the cluster-enhanced sparse approximation (CESA) method for estimating overlapping ultrasonic echoes. CESA is specifically adapted to deal with a large number of signals acquired during an ultrasonic scan. It incorporates two principal algorithms. The first is a clustering algorithm, which divides a set of signals comprising an ultrasonic scan into groups of signals that can be approximated by the same set of atoms. The second is a two-stage iterative algorithm, which alternates between update of the atoms associated with each cluster, and re-clustering of the signals according to the updated atoms. Because CESA operates on clusters of signals, it achieves improved results in terms of approximation error and computation time compared with conventional sparse methods, which operate on each signal separately. The superior ability of CESA to approximate highly overlapping ultrasonic echoes is demonstrated through simulation and experiments on adhesively bonded structures.

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Section: B Improving the Approximationmentioning

confidence: 99%

Section: B Improving the Approximationmentioning

confidence: 99%