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Reseach Article

Interval Dependant Thresholding based De-noising of Ultrasonic TOFD Signals from Austenitic Stainless Steel Welds

by Angam Praveen, K. Vijayarekha, B. Venkatraman
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 72 - Number 2
Year of Publication: 2013
Authors: Angam Praveen, K. Vijayarekha, B. Venkatraman
10.5120/12463-8827

Angam Praveen, K. Vijayarekha, B. Venkatraman . Interval Dependant Thresholding based De-noising of Ultrasonic TOFD Signals from Austenitic Stainless Steel Welds. International Journal of Computer Applications. 72, 2 ( June 2013), 1-5. DOI=10.5120/12463-8827

@article{ 10.5120/12463-8827,
author = { Angam Praveen, K. Vijayarekha, B. Venkatraman },
title = { Interval Dependant Thresholding based De-noising of Ultrasonic TOFD Signals from Austenitic Stainless Steel Welds },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 72 },
number = { 2 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume72/number2/12463-8827/ },
doi = { 10.5120/12463-8827 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:36:49.606219+05:30
%A Angam Praveen
%A K. Vijayarekha
%A B. Venkatraman
%T Interval Dependant Thresholding based De-noising of Ultrasonic TOFD Signals from Austenitic Stainless Steel Welds
%J International Journal of Computer Applications
%@ 0975-8887
%V 72
%N 2
%P 1-5
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Austenitic stainless steel has structural values in almost all industries. It is one of the most widely used materials. Qualitative assessment of such important components is of greater importance in very sensitive applications such as nuclear reactor vessels. Ultrasonic based Time of Flight diffraction is a reliable technique in testing the materials for many types of defects in welds. Echo signals obtained by the receiver are also accompanied by ambient scattering noise due to the signal interaction with the grains of the material. This noise degrades the quality of the defect echo signal and at times completely deteriorates the shape of the defect signal there by making it unsuitable for characterization. Signal processing is a necessary aspect in restoring the defect signal's shape, size etc for proper detection and positioning of the defect in the material. Wavelet Transform is one such popular technique for de-noising of the signals in which thresholding of high frequency components removes the unwanted noise. Conventional global thresholding gives good improvement in SNR values. This paper implements an Interval dependant thresholding method and it is found that it has very good improvement in SNR values compared to conventional techniques.

References
  1. R. Drai , F. Sellidj, M. Khelil, A. Benchaala, "Elaboration of some signal processing algorithms in ultrasonic techniques: application to materials NDT", Ultrasonics, Algeria, 2000, vol no. 38, pg no. 503-507
  2. T. Bouden,S. Dib, K. Aissaous and M. Grimes, "Signal Processing Methods for Materials Defects Detection", IEEE Ultrasonic Symposium, Jijel, Algeria, 2009
  3. L. Ericsson , T. Stepinski, "Algorithms for suppressing ultrasonic backscattering from material structure", Ultrasonics, ELSEVIER, Sweden, 2002, vol. no. 40,pg no. 733–734
  4. V. L. Newhouse, N. M. Bilgutay, J. Saniie and E. S. Furgason, "Flaw-to-grain echo enhancement by split spectrum processing", Ultrasonics, March 1982, pp. 59-68.
  5. Scott E Bailey, "Implementing SSP in TMS320c26", Texas Instruments, 1997.
  6. Temple J. A. G. , "Time-of-flight inspection: theory", Nulcear Energy, 1983, 22, No. 5, Oct. , pp 335-348.
  7. Ogilvy J. A. and Temple J. A. G. , "Diffraction of elastic waves by cracks: Application of time of flight inspection", Ultrasonics, Nov. 1983, pp 259-268.
  8. Verkooijen J. , "TOFD used to replace radiography", Insight Vol. 37. No. 6, June 1995, pp 433-435.
  9. Silk M. G. , "An evaluation of the performance of the TOFD techniques as a means of sizing flaws, with particular reference to flaws with curved profiles", Insight vol. 38, No. 4, April, 1996.
  10. Sony Baby, Balasubramaniam T. , Pardikar R. J. , Palaniyappan M. and Subbaratnam R. , "Time of flight diffraction(TOFD) technique for accurate sizing if cracks embedded in sub-cladding", Insight, Vol. 45, No. 9, September, 2003.
  11. Predrag Duki?, Ines Duki?, "Advantages of ultrasonic time of flight diffraction technique and R6 structural integrity assessment procedure for nuclear power plant components", International Conference Nuclear Energy in Central Europe 2000, Slovenia
  12. M. Riahi and M. R. Abolhasany, "Substitution of the Time-of-Flight Diffraction Technique for Nondestructive Testing of Welds and Thick Layers of Steel: A Comparative Investigation", Russian Journal of Nondestructive Testing, Tehran, Iran Vol. 42, No. 12, 794–801
  13. Tianlu Chen, Peiwen Que, Oi Zhang, and Qingkun Liu, "Ultrasonic Nondestructive Testing Accurate Sizing and Locating Technique Based on Time-of-Flight-Diffraction Method", Russian Journal of Nondestructive Testing, 2005, Shanghai, China, Vol. 41, No. 9, 57-68, 594–601
  14. Robi Polikar, "The Story of Wavelets", IEEE CSCC'99 Proceedings, USA, 1999, 5481-5486.
  15. Gaohua Liao, Dehui Liu, "Time Frequency Neighborhood Signals De-noise Method in Ultrasonic Inspection", International Conference on Measuring Technology and Mechatronics Automation, Nanchang, China, 2009
  16. J. C. Lázaro,J. L. San Emeterio and A. Ramos, "Noise Reduction in Ultrasonic NDT using Discrete Wavelet Transform Processing", IEEE Ultrasonic Symposium, Spain, 2002, pg no. 777-780
  17. Zahra Talebhaghighi, Farnaz Bazzazi,Ali sadr, "Design and Simulation of Ultrasonic Denoising Algorithm Using Wavelet Transform and ICA", IEEE, 2010, Vol. 1, pg no. 739-743
  18. M. Kreidl, P. Houfek, "Reducing Ultrasonic Signal Noise by Algorithms based on Wavelet Thresholding", Acta Polytechnica, 2002, Vol. 42 no. 2
  19. Yuan Chen,Hongwei Ma, "Application of wavelet analysis to signal de-noising in ultrasonic testing of welding flaws", 17th World Conference on Nondestructive Testing, Shanghai, China, 2008
  20. Erdal Oruklu and Jafar Saniie, "Ultrasonic flaw detection using Discrete Wavelet Transform for NDT applications", IEEE Ultrasonic Symposium, Illinois Institute of Technology Chicago, 2004, 1054-1057
  21. Zhen-zhu Yu,Chong Zhao,Wei Ma, "Application of the Wavelet Transform in Ultrasonic Echo Signal Processing", IEEE Computer Society, Beijing, China, 2009, 576-579.
  22. Gaohua Liao, Junmei Xi, "Ultrasonic Testing Signal Processing of Weld Flaw Based on the Second Generation Wavelet", 9th International Conference on Hybrid Intelligent Systems, Nanchang, China, 2009
  23. Xianfeng Fan, Ming J Zuo, and Xiaodong Wang, "Application of Stationary Wavelet Transforms to Ultrasonic Crack Detection", IEEE, Canada
  24. O. Tumšys, R. Raišutis, "Reduction of a structural noise by application of the wavelet transform with level-dependent thresholds", ULTRAGARSAS Journal, NDT. net, Lithuania, Nr. 1(62), 2007, pg no. 18-23
  25. Gang Li,"Noise Removal of Raman Spectra using Interval thresholing Method", Second International Symposium on intelligent Information Technology Application, 2008, IITA'08, Shanghai, China, Vol. 1, pg no. 535-539
  26. P. Karpur, P. M. Shankar, J. L. Rose and V. L. Newhouse, 'Split Spectrum Processing: Determination of available bandwidth for spectral splitting' Ultrasonics 1988, Vol. 26,204-209.
Index Terms

Computer Science
Information Sciences

Keywords

Interval Dependant Thresholding TOFD Discrete Wavelet Transform Signal-to-Noise Ratio