Signal matching wavelet for ultrasonic flaw detection in high background noise

The wavelet transform (WT) is widely used in ultrasonic flaw detection (UFD) systems because of its property of multiresolution time-frequency analysis. Those traditional WT-based methods for UFD use a wavelet basis with limited types to match various echo signals (called wavelet matching signals), so it is difficult for those methods to achieve the optimal match between echo signal and wavelet basis. This results in limited detection ability in high background noise for those WT-based methods. In this paper, we propose a signal matching wavelet (SMW) method for UFD to solve this problem. Unlike traditional UFD systems, in the proposed SMW, the transmitted signal is designed to be a wavelet function for matching a wavelet basis. This makes it possible to obtain the optimal match between the echo signal and the wavelet basis. To achieve the optimal match from the aspect of energy, we derive three rules for designing the transmitted signal and selecting the wavelet basis. Further, the parameter selection in applying the proposed SMW method to a practical UFD system is analyzed. In addition, a low-rate discrete WT structure is designed to decrease the hardware cost, which facilitates the practical application of the proposed SMW. The simulation results show that the proposed SMW can efficiently detect flaws in high background noise even with SNR lower than -20 dB, outperforming the existing methods by 5 dB.

[2]  Yong Yang,et al.  Research on Ultrasonic Detection of Seabed Oil Pipeline Based on Wavelet Packet De-Noising , 2009, 2009 5th International Conference on Wireless Communications, Networking and Mobile Computing.

[3]  M.G. Gustafsson,et al.  Nonlinear clutter suppression using split spectrum processing and optimal detection , 1996, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[4]  Pei-wen Que,et al.  Wavelet based noise suppression technique and its application to ultrasonic flaw detection. , 2006, Ultrasonics.

[5]  Pasquale Daponte,et al.  An improved method for automatic detection and location of defects in electronic components using scanning ultrasonic microscopy , 2003, IEEE Trans. Instrum. Meas..

[6]  Gordon Hayward,et al.  The modelling and design of controllable composite transducers , 1990, IEEE Symposium on Ultrasonics.

[7]  Shiv Dutt Joshi,et al.  A new approach for estimation of statistically matched wavelet , 2005, IEEE Transactions on Signal Processing.

[8]  A Ramos,et al.  Noise reduction in ultrasonic NDT using undecimated wavelet transforms. , 2006, Ultrasonics.

[9]  A. Abbate,et al.  Signal detection and noise suppression using a wavelet transform signal processor: application to ultrasonic flaw detection , 1997, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[10]  S. Mallat A wavelet tour of signal processing , 1998 .

[11]  Qi Tian,et al.  Statistical analysis of split spectrum processing for multiple target detection , 1998, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[12]  Daniel Massicotte,et al.  Wavelet-transform-based method of analysis for Lamb-wave ultrasonic NDE signals , 2000, IEEE Trans. Instrum. Meas..

[13]  G. Hayward,et al.  A theoretical approach for inverse filter design in ultrasonic applications , 1989, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[14]  Ren-Jean Liou,et al.  Flaw detection and sizing of ultrasonic images using wavelet transform and SAFT , 2004, Proceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, 2004. ISPACS 2004..

[15]  Nihat M. Bilgutay,et al.  Flaw detection in stainless steel samples using wavelet decomposition , 1994, 1994 Proceedings of IEEE Ultrasonics Symposium.

[16]  J. Saniie,et al.  Ultrasonic flaw detection using discrete wavelet transform for NDE applications , 2004, IEEE Ultrasonics Symposium, 2004.

[17]  Deepen Sinha,et al.  On the optimal choice of a wavelet for signal representation , 1992, IEEE Trans. Inf. Theory.

[18]  Raghuveer M. Rao,et al.  Algorithms for designing wavelets to match a specified signal , 2000, IEEE Trans. Signal Process..

[19]  Pankaj K. Das,et al.  Application of wavelet transform signal processor to ultrasound , 1994, 1994 Proceedings of IEEE Ultrasonics Symposium.

[20]  P. Vaidyanathan Multirate Systems And Filter Banks , 1992 .

[21]  B. Molavi,et al.  Design of Optimum Wavelet for Noise Suppression and its Application to Ultrasonic Echo Delay Estimation , 2007, 2007 IEEE International Conference on Signal Processing and Communications.

[22]  David L. Donoho,et al.  De-noising by soft-thresholding , 1995, IEEE Trans. Inf. Theory.