TY - JOUR
T1 - Digital signal processing methods for ultrasonic echoes
AU - Sinding, Kyle M.
AU - Drapaca, Corina S.
AU - Tittmann, Bernhard R.
N1 - Publisher Copyright:
© 1986-2012 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2016/8
Y1 - 2016/8
N2 - Digital signal processing has become an important component of data analysis needed in industrial applications. In particular, for ultrasonic thickness measurements, the signal-to-noise ratio (SNR) plays a major role in the accurate calculation of the arrival time. For this application, a bandpass filter is not sufficient since the noise level cannot be significantly decreased such that a reliable thickness measurement can be performed. This paper demonstrates the abilities of two regularization methods - total variation (TV) and Tikhonov - to filter acoustic and ultrasonic signals. Both of these methods are compared with frequency-based filtering for digitally produced signals as well as signals produced by ultrasonic transducers. This paper demonstrates the ability of the TV and Tikhonov filters to accurately recover signals from noisy acoustic signals faster than a bandpass filter. Furthermore, the TV filter has been shown to reduce the noise of a signal significantly for the signals with clear ultrasonic echoes. SNRs have been increased over 400% by using simple parameter optimization. While frequency-based filtering is efficient for specific applications, this paper shows that the reduction of noise in ultrasonic systems can be much more efficient with regularization methods.
AB - Digital signal processing has become an important component of data analysis needed in industrial applications. In particular, for ultrasonic thickness measurements, the signal-to-noise ratio (SNR) plays a major role in the accurate calculation of the arrival time. For this application, a bandpass filter is not sufficient since the noise level cannot be significantly decreased such that a reliable thickness measurement can be performed. This paper demonstrates the abilities of two regularization methods - total variation (TV) and Tikhonov - to filter acoustic and ultrasonic signals. Both of these methods are compared with frequency-based filtering for digitally produced signals as well as signals produced by ultrasonic transducers. This paper demonstrates the ability of the TV and Tikhonov filters to accurately recover signals from noisy acoustic signals faster than a bandpass filter. Furthermore, the TV filter has been shown to reduce the noise of a signal significantly for the signals with clear ultrasonic echoes. SNRs have been increased over 400% by using simple parameter optimization. While frequency-based filtering is efficient for specific applications, this paper shows that the reduction of noise in ultrasonic systems can be much more efficient with regularization methods.
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U2 - 10.1109/TUFFC.2016.2557283
DO - 10.1109/TUFFC.2016.2557283
M3 - Article
C2 - 28113550
AN - SCOPUS:84981320698
VL - 63
SP - 1172
EP - 1176
JO - IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
JF - IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
SN - 0885-3010
IS - 8
M1 - 7462300
ER -