Chirplet Transform in Ultrasonic Non-Destructive Testing and Structural Health Monitoring: A Review
Abstract
Ultrasonic non-destructive testing signal can be decomposed into a set of chirplet signals, which makes the chirplet transform a fitting ultrasonic signal analysis and processing method. Moreover, compared to wavelet transform, short-time Fourier transform and Gabor transform, chirplet transform is a comprehensive signal approximation method, nevertheless, the former methods gained more popularity in the ultrasonic signal processing research. In this paper, the principles of the chirplet transform are explained with a simplified presentation and the studies that used the transform in ultrasonic non-destructive testing and in structural health monitoring are reviewed to expose the existing applications and motivate the research in the potential ones.
Keywords:
chirplet tranform, ultrasonic, guided wave, NDT, structural health monitoringDownloads
References
P. J. Shull, Nondestructive Evaluation: Theory, Techniques and Applications, Marcel Dekker, 2001 DOI: https://doi.org/10.1201/9780203911068
C. Hellier, Handbook of Nondestructive Evaluation, McGraw-Hill, 2003
American Society for Nondestructive Testing, Nondestructive Testing Handbook Volume 7: Ultrasonic Testing, Columbus, 2007
L. W. Schmerr. Jr, J. S. Song, Ultrasonic Nondestructive Evaluation Systems: Models and Measurements, Springer, 2007 DOI: https://doi.org/10.1007/978-0-387-49063-2
Z. Su, L. Ye, Identification of Damage Using Lamb Waves, Vol. 48, Springer London, 2009 DOI: https://doi.org/10.1007/978-1-84882-784-4
S. K. Sin, C. H. Chen, “A comparison of deconvolution techniques for the ultrasonic nondestructive evaluation of materials”, IEEE Transactions on Image Processing, Vol. 1, No. 1, pp. 3-10, 1992 DOI: https://doi.org/10.1109/83.128026
F. Honarvar, H. Sheikhzadeh, M. Moles, A. N. Sinclair, “Improving the time-resolution and signal-to-noise ratio of ultrasonic NDE signals”, Ultrasonics, Vol. 41, No. 9, pp. 755-763, 2004 DOI: https://doi.org/10.1016/j.ultras.2003.09.004
H. Jin, K. Yang, S. Wu, H. Wu, J. Chen, “Sparse deconvolution method for ultrasound images based on automatic estimation of reference signals”, Ultrasonics, Vol. 67, pp. 1–8, 2016 DOI: https://doi.org/10.1016/j.ultras.2015.12.011
S. J. Mirahmadi, F. Honarvar, “Application of signal processing techniques to ultrasonic testing of plates by S0 Lamb wave mode”, NDT & E International, Vol. 44, No. 1, pp. 131-137, 2011 DOI: https://doi.org/10.1016/j.ndteint.2010.10.004
E. P. de Moura, M. H. S. Siqueira, R. R. da Silva, J. M. A. Rebello, L. P. Caloba, “Welding defect pattern recognition in TOFD signals Part 1. Linear classifiers”, Insight-Non-Destructive Testing and Condition Monitoring, Vol. 47, No. 12, pp. 777-782, 2005 DOI: https://doi.org/10.1784/insi.2005.47.12.777
S. L. S.Lalithakumari, B. S. B.Sheelarani, B. V. B.Venkatraman, “Artificial Neural Network based Defect Detection of Welds in TOFD Technique”, International Journal of Computer Applications, Vol. 41, No. 20, pp. 17-20, 2012 DOI: https://doi.org/10.5120/5808-8069
G. K. Sharma, S. Bhagi, S. Thirunavukkarasu, B. P. Rao, “Wavelet transform-based approach for processing ultrasonic B-scan images”, Insight-Non-Destructive Testing and Condition Monitoring, Vol. 59, No. 2, pp. 93-99, 2017 DOI: https://doi.org/10.1784/insi.2017.59.2.93
M. S. Mohammed, K. Ki-Seong, “Signal conditioning for the recursive least-squares filter in ultrasonic testing of materials”, Insight-Non-Destructive Testing and Condition Monitoring, Vol. 59, No. 11, pp. 591-595, 2017 DOI: https://doi.org/10.1784/insi.2017.59.11.591
M. S. Mohammed, K. Ki-Seong, “Shift-invariant wavelet packet for signal de-noising in ultrasonic testing”, Insight-Non-Destructive Testing and Condition Monitoring, Vol. 54, No. 7, pp. 366-370, 2012 DOI: https://doi.org/10.1784/insi.2012.54.7.366
M. S. Mohammed, K. Ki-Seong, “Improving an adaptive filtering system for ultrasonic testing”, Insight-Non-Destructive Testing and Condition Monitoring, Vol. 56, No. 5, pp. 240-245, 2014 DOI: https://doi.org/10.1784/insi.2014.56.5.240
W. H. Prosser, M. D. Seale, B. T. Smith, “Time-frequency analysis of the dispersion of Lamb modes The Journal of the Acoustical Society of America, Vol. 105, No. 5, pp. 2669-2676, 1999 DOI: https://doi.org/10.1121/1.426883
M. Niethammer, L. J. Jacobs, J. Qu, J. Jarzynski, “Time-frequency representations of Lamb waves”, The Journal of the Acoustical Society of America, Vol. 109, No. 5, pp. 1841-1847, 2001 DOI: https://doi.org/10.1121/1.1357813
L. De Marchi, A. Marzani, S. Caporale, N. Speciale, “Ultrasonic guided-waves characterization with warped frequency transforms”, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 56, No. 10, pp. 2232-2240, 2009 DOI: https://doi.org/10.1109/TUFFC.2009.1305
S. Mann, S. Haykin, “The Chirplet Transform : A Generalization of Gabor’ s Logon Transform”, Vision Interface, Vol. 91, pp. 205-212, 1991
S. Mann, S. Haykin, “Chirplets’ and ‘warblets’: novel time–frequency methods”, Electronics Letters, Vol. 28, No. 2, pp. 114-116, 1992 DOI: https://doi.org/10.1049/el:19920070
S. Mann, S. Haykin, “The chirplet transform: physical considerations”, IEEE Transactions on Signal Processing, Vol. 43, No. 11, pp. 2745-2761, 1995 DOI: https://doi.org/10.1109/78.482123
S. Mann, “Adaptive “chirplet” transform: an adaptivegeneralization of the wavelet transform”, Optical Engineering, Vol. 31, No. 6, pp. 1243-1256, 1992 DOI: https://doi.org/10.1117/12.57676
Y. Lu, R. Demirli, “Chirplet transform for ultrasonic signal analysis and NDE applications”, IEEE Ultrasonics Symposium, Rotterdam, The Netherlands, March 6, 2006
Y. Lu, R. Demirli, G. Cardoso, J. Saniie, “A successive parameter estimation algorithm for chirplet signal decomposition”, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 53, No. 11, pp. 2121-2131, 2006 DOI: https://doi.org/10.1109/TUFFC.2006.152
R. Demirli, J. Saniie, “Model-based estimation of ultrasonic echoes. Part I: Analysis and algorithms”, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 48, No. 3, pp. 787-802, 2001 DOI: https://doi.org/10.1109/58.920713
R. Demirli, J. Saniie, “Model-based estimation of ultrasonic echoes. Part II: Nondestructive evaluation applications”, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 48, No. 3, pp. 803-811, 2001 DOI: https://doi.org/10.1109/58.920714
Y. Lu, E. Oruklu, J. Saniie, “Chirplet Signal and Empirical Mode Decompositions of Ultrasonic Signals for Echo Detection and Estimation”, Journal of Signal and Information Processing, Vol. 4, No. May, pp. 149-157, 2013 DOI: https://doi.org/10.4236/jsip.2013.42022
Y. Lu, R. Demirli, E. Oruklu, J. Saniie, “Estimation and classification of ultrasonic echoes backscattered from reverberant multilayered materials”, International Congress on Ultrasonics, Vienna, Austria, April 9-13, 2007 DOI: https://doi.org/10.3728/ICUltrasonics.2007.Vienna.1493_lu
J. C. Hong, K. H. Sun, Y. Y. Kim, “Dispersion-based short-time Fourier transform applied to dispersive wave analysis”, The Journal of the Acoustical Society of America, Vol. 117, No. 5, pp. 2949-2960, 2005 DOI: https://doi.org/10.1121/1.1893265
H. Kuttig, M. Niethammer, S. Hurlebaus, L. J. Jacobs, “Model-based analysis of dispersion curves using chirplets”, The Journal of the Acoustical Society of America, Vol. 119, No. 4, pp. 2122-2130, 2006 DOI: https://doi.org/10.1121/1.2177587
S. G. Mallat, Z. Zhang, “Matching pursuits with time-frequency dictionaries”, IEEE Transactions on Signal Processing, Vol. 41, No. 12, pp. 3397-3415, 1993 DOI: https://doi.org/10.1109/78.258082
A. Raghavan, C. E. S. Cesnik, “Guided-wave signal processing using chirplet matching pursuits and mode correlation for structural health monitoring”, Smart Materials and Structures, Vol. 16, No. 2, pp. 355-366, 2007 DOI: https://doi.org/10.1088/0964-1726/16/2/014
H. Zhang, C. E. S. Cesnik, “Damage characterization based on nonlinear guided wave simulation and chirplet matching pursuit algorithm”, Health Monitoring of Structural and Biological Systems XII, Denver, USA, March 4-8, 2018 DOI: https://doi.org/10.1117/12.2295117
F. Kerber, H. Sprenger, M. Niethammer, K. Luangvilai, L. J. Jacobs, “Attenuation Analysis of Lamb Waves Using the Chirplet Transform”, EURASIP Journal on Advances in Signal Processing, Vol. 2010, No. 1, 2010 DOI: https://doi.org/10.1155/2010/375171
C. Y. Kim, K. J. Park, “Mode separation and characterization of torsional guided wave signals reflected from defects using chirplet transform”, NDT & E International, Vol. 74, pp. 15-23, 2015 DOI: https://doi.org/10.1016/j.ndteint.2015.04.006
J. C. O’Neill, P. Flandrin, W. C. Karl, “Sparse representations with chirplets via maximum likelihood estimation”, IEEE Transactions on Signal Processing, Vol. 48, pp. 42-53, 2000
C. Y. Kim, K. J. Park, “Characterization of Pipe Defects in Torsional Guided Waves Using Chirplet Transform”, Transactions of the Korean Society for Noise and Vibration Engineering, Vol. 24, No. 8, pp. 636–642, 2014 DOI: https://doi.org/10.5050/KSNVE.2014.24.8.636
Y. W. Kim, K.J. Park, “Application of chirplet transform for detecting axial cracks in pipes using torsional guided modes”, Insight-Non-Destructive Testing and Condition Monitoring, Vol. 59, No. 3, pp. 138-143, 2017 DOI: https://doi.org/10.1784/insi.2017.59.3.138
L. Zeng, M. Zhao, J. Lin, W. Wu, “Waveform separation and image fusion for Lamb waves inspection resolution improvement”, NDT & E International, Vol. 79, pp. 17-29, 2016 DOI: https://doi.org/10.1016/j.ndteint.2015.11.006
Downloads
How to Cite
License
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
