PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Novel S-transform information fusion for filtering ultrasonic pulse-echo signals

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
PL
Nowa metoda filtrowania sygnału ultradźwiękowego bazująca na transformacie S i fuzji informacji
Języki publikacji
EN
Abstrakty
EN
Direct evaluation of ultrasonic signals requires data analyses with an acceptable level of noise. Ultrasonic signals represent a specific category of time domain signals to be analyzed. In order to increase a difference between the level of noise and the amplitude of the ultrasonic pulse a suitable method for signal filtering has to be used. Within this article we discuss and evaluate a novel signal denoising method. The S-transform for signal analysis and processing was used. This transformation has been recently introduced for ultrasonic echo analyses. Proposed transformation represents an intermediate stage between the Fourier transform analysis and the wavelet transform analysis. In order to filter ultrasonic signals from the Electromagnetic Acoustic Transducer (EMAT) with a high level of noise, new, different approach in signal filtering was developed based on an information fusion. Suggested method is able to process the pulse-echo signal in its full complexity. Proposed method offers good results in studied ultrasonic signals in comparison to digital filter or wavelet denoising.
PL
Bezpośrednia ocean sygnału ultradźwiękowego wymaga analizy danych obciążonych szumami. W celu zwiększenia różnicy między amplitudą sygnału a szumami użyto specjalnej metody filtrowania. Zastosowano transformatę S do analizy ultradźwiękowego sygnału echa. Tego typu transformata jest metodą pośrednia między transformatą Fouriera a transformatą falkową. Użyto nowej metody bazującej na fuzji informacji. Testy potwierdziły że nowa metoda może być skuteczniejsza niż filtrowanie cyfrowe czy odszumianie falkowe.
Rocznik
Strony
290--295
Opis fizyczny
Bibliogr. 24 poz., rys.
Twórcy
autor
autor
autor
autor
  • Aeronautical Systems, Instrumentation, Diagnostics, Nondestructive Testing and Signal Processing laboratory, Department of measurement, Czech Technical University, Faculty of Electrical Engineering, Technicka 2,166 27, Prague, michal.kubinyi@fel.cvut.cz
Bibliografia
  • [1] S. Starman: Utility design of EMAT probe, n. 20278, Industrial Property office of Czech Republic, 2009.
  • [2] Masahiko Hirao and Hirotsugu Ogi: EMATS for Science and Industry: Noncontacting Ultrasonic Measurements, Kluwer Academic Publishers Group, Netherlands, 2003.
  • [3] K.F. Graff: Wave Motion in Elastic Solids, Dover Publications, pp. 213-257. 1991
  • [4] N. M. Bilgutay, U. Bencharit, J. Saniie: Enhancement ultrasonic imaging with split-spectrum processing and polarity thresholding, IEEE Transactions on Acoustics, Speech and Signal Processing, vol. 37, no. 10, pp. 1590-1592, 1989.
  • [5] A. Hoess and H. Ermer: Adaptive Wiener filtering for B-mode image improvement, IEEE Ultrasonics Symposium Proceedings, vol. 2, pp. 1219-1222, 1992.
  • [6] I. Daubechies: Orthonormal Bases of Compactly Supported Wavelets, Communications on Pure and Applied Mathematics, vo. 41, no. 7, pp. 909-996, 1988.
  • [7] D.L. Donoho and I.M. Johnstone: Adapting to Unknown Smoothness via Wavelet shrinkage, Journal of the American Statistical Association, vol. 90, no. 432, pp. 1200-1224, 1995.
  • [8] A. Abbate and J. Koay: Signal detection and noise suppression using a wavelet transform signal processor: application to ultrasonic flaw detection, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, vol. 44, no. 1, pp. 14-26, 1997.
  • [9] F.J. Harris: On the use of windows for harmonic analysis with the discrete Fourier Transform, Proc. IEEE, vol. 66, no. 1, pp. 51-83, 1978.
  • [10] R. Stockwell: A basis for efficient representation of the S-transform, Digital Signal processing, vol. 17, no. 1, pp. 371- 393, 2007.
  • [11] Soo-Chang Pei and Pai-Wei Wang: Novel Inverse S Transform With Equalization Filter, IEEE Transactions on Signal Processing, vol. 57, no. 10, pp. 3858-3868, 2009.
  • [12] Robert A. Brown, M. Louis Lauzon and Richard Frayne: A General Description of Linear Time-Frequency Transforms and Formulation of a Fast, Invertible Transform That Samples the Continuous S-Transform Spectrum Nonredundantly, IEEE Transactions on Signal Processing, vol. 58, no. 1, pp. 281-290, 2010.
  • [13] Song Shou-Peng and Que Pei-Wen: Wavelet Based Noise Suppression Technique and Its Application to Ultrasonic Flaw Detection, Ultrasonics, vol. 4, pp. 188-193, 2006.
  • [14] S. M. Kay: Fundamentals of statistical signal processing: estimation theory, Prentice-Hall, 625 pp., 1993
  • [15] H. Vincent Poor: An Introduction to Signal Detection and Estimation, Springer-Verlag New York, 1994.
  • [16] M. Kubínyi: Sensitivity Increasing of an Ultrasonic EMAT Materiology, AIAA-Pegasus Conference Proceedings, Naples, 2007.
  • [17] M. Schimmel and J. Gallart: The Inverse S-Transform in Filters With Time-Frequency Localization, IEEE Transactions on Signal Processing, vol. 53, no. 11, pp. 4417-4422, 2005.
  • [18] Soo-Chang Pei and Pai-Wei Wang: Novel inverse S-Transform with equalization filter, IEEE Transactions on Signal Processing, vol. 57, no. 10, pp. 3858-3868, 2009.
  • [19] M. Vetterli and C. Herley: Wavelets and Filter Banks: Theory and Design, IEEE Transactions on Signal Processing, vol. 40, no. 9, pp. 2207-2232, 1992.
  • [20] R. Stockwell, L. Mansinha and R. Lowe: Localization of the complex spectrum: the S-transform, IEEE Transactions on Signal Processing, vol. 44, no. 4, pp. 998 –1001, 1996.
  • [21] M. Schimmel and J. Gallart: The inverse s-transform in filters with time-frequency localization, IEEE Transactions on Signal Processing, vol. 53, no. 11, pp. 4417 – 4422, 2005.
  • [22] S.-C. Pei and P.-W.Wang: Novel inverse S-transform with equalization filter, IEEE Transactions on Signal Processing, vol. 57, no. 10, pp. 3858 –3868, 2009.
  • [23] David L. Donoho: Adapting to unknown smoothness via wavelet shrinkage, Tech. rep., Stanford University, 1994
  • [24] V. Matz, R. Smid, S. Starman, M. Kreidl: Signal-to-noise ratio enhancement based on wavelet filtering in ultrasonic testing, Ultrasonics, vol. 49, no. 8, pp. 752 – 759, 2009.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPW8-0016-0091
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.