Article Article
Quality Assurance of Thin-Walled Nickel Tubes by Eddy Current (EC) Testing Using the Discrete Wavelet Transform (DWT) Processing Methodology

In this study, the discrete wavelet transform (DWT)-based signal processing methodology is applied for eliminating noise due to permeability variations in saturation eddy current (EC) testing signals from nickel tubes. The nickel tubes are of 0.3mmthickness and 6.6mmouter diameter. Systematic studies have been carried out to optimize the wavelet functions, number of decomposition levels, and thresholding algorithm for DWT processing based on the signal-to-noise ratio (SNR). The DWT processing has enabled reliable detection of a 0.1mmdeep notch located on the inner surface of the tubes meeting its stringent quality requirements. Application of signal processing-based methodology has resulted in an improvement in SNR of 11.4 dB as against 5.1 dB for the raw signals.

DOI: https://doi.org/10.1080/09349847.2020.1868639

References

S. Thirunavukkarasu et al., Insight Br. J. Non-Destr. Test. Condition Monit. 46 (9), 533–536 (Sept. 2004). DOI: 10.1784/insi.46.9.533.40839.

B. P. C. Rao et al., Insight Br. J. Non-Destr. Test. Condition Monit. 49, 698–700 (2007). DOI: 10.1784/insi.2007.49.12.698.

ASTM standard E 213-20, Standard Practice for Ultrasonic Examination of Metal Pipe and Tubing.

ASTM standard E 309-16, Standard Practice for Eddy Current Examination of Steel Tubular Products Using Magnetic Saturation.

B. Sasi et al., J. Nondestruct. Test. Eval. 21 (1), 41–46 (2001).

S. S. Udpa and P. O. Moore, Nondestructive Testing Handbook- Electromagnetic Testing, 3 ed. (ASNT, 2004), Vol. 5.

S. S. Udpa, Signal Proc. Pattern Recog. Nondestruct. Eval. Mat. 44, 129–144 (1988).

S. Tian et al., Nucl. Eng. Des. 245, 78–88 (2012). DOI: 10.1016/j.nucengdes.2011.12.033.

A. Sophian et al., NDT E Int. 36 (1), 37–413 (2003). DOI: 10.1016/S0963-8695(02)00069-5.

G. Y. Tian et al., IEE Proc. - Sci. Meas. Technol. 152 (4), 141–148 (2005). DOI: 10.1049/ip-smt:20045011.

S.-F. Chuang, J. P. Basan, and J. C. Moulder, Rev. Prog. Quant. Nondestr. Eval. 17, 775–781 (1998).

G. Chen, A. Yamaguchi, and K. Miya, IEEE Trans. Magn. 34 (3), 642–648 (1998). DOI: 10.1109/20.668059.

L. A. N. M. Lopez, D. K. S. Ting, and B. R. Upadhyaya, Prog. Nucl. Energy 50, 828–835 (2008). DOI: 10.1016/j.pnucene.2007.07.008.

B. Sasi et al.,Res. Nondestruct. Eval. 21 (3), 157–170 (2010). DOI: 10.1080/09349847.2010.488799.

X.-L. Li and J.-L. Sun, Adv. Mater. Res. 986-987, 1461–1465 (2014). DOI: 10.4028/www.scientific.net/AMR.986-987.1461.

S. G. Mallat, IEEE Trans. Pattern Anal. Mach. Intell. 11 (7), 674–693 (1989). DOI: 10.1109/34.192463.

S. Thirunavukkarasu et al.,Ann. Nucl. Energy 38, 817–824 (2011). DOI: 10.1016/j.anucene.2010.11.015.

D. L. Donoho, IEEE Trans. Inform. Theory 41 (3), 613–627 (1995 May). 10.1109/18.382009.

D. Valencia et al., IEEE Symposium on Signal Processing, Images and Artificial Vision, Colombia, 2016.

 

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