Abstract
The noise as an undesired phenomenon often appears in the pulsed eddy current testing (PECT) signal, and it is difficult to recognize the character of the testing signal. One of the most common noises presented in the PECT signal is the Gaussian noise, since it is caused by the testing environment. A new denoising approach based on singular value decomposition (SVD) is proposed in this paper to reduce the Gaussian noise of PECT signal. The approach first discusses the relationship between signal to noise ratio (SNR) and negentropy of PECT signal. Then the Hankel matrix of PECT signal is constructed for noise reduction, and the matrix is divided into noise subspace and signal subspace by a singular valve threshold. Based on the theory of negentropy, the optimal matrix dimension and threshold are chosen to improve the performance of denoising. The denoised signal Hankel matrix is reconstructed by the singular values of signal subspace, and the denoised signal is finally extracted from this matrix. Experiment is performed to verify the feasibility of the proposed approach, and the results indicate that the proposed approach can reduce the Gaussian noise of PECT signal more effectively compared with other existing approaches.
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XU Z Y, WU X J, LI J, et al. Assessment of wall thinning in insulated ferromagnetic pipes using the time to-peak of differential pulsed eddy current testing signals [J]. NDT & E International, 2012, 51: 24–29.
ALAMIN M, TIAN G Y, ANDREWS A, et al. Principal component analysis of pulsed eddy current response from corrosion in mild steel [J]. IEEE Sensors Journal, 2012, 12(8): 2548–2553.
ANGANI C S, PARK D G, KIM C G, et al. The pulsed eddy current differential probe to detect a thickness variation in an insulated stainless steel [J]. Journal of Nondestructive Evaluation, 2010, 29: 248–252.
CHENG W Y. Pulsed eddy current testing of carbon steel pipes wall-thinning through insulation and cladding [J]. Journal of Nondestructive Evaluation, 2012, 31: 215–224.
MUKRIZ I, TIAN G Y, LI Y. 3D transient magnetic field mapping for angular slots in aluminium [J]. Insight, 2009, 51(1): 21–24.
KIWA T, HAYASHI T, KAWASAKI Y, et al. Magnetic thickness gauge using a Fourier transformed eddy current technique [J]. NDT & E International, 2009, 42: 606–609.
HE Y Z, LUO F L, PAN M C. Defect characterization based on pulsed eddy current imaging technique [J]. Sensors and Actuators A, 2010, 164: 1–7.
HOSSEINI S, LAKIS A A. Application of time frequency analysis for automatic hidden corrosion detection in a multilayer aluminum structure using pulsed eddy current [J]. NDT & E International, 2012, 47: 70–79.
THEODOULIDIS T, WANG H T, TIAN G Y. Extension of a model for eddy current inspection of cracks to pulsed excitations [J]. NDT & E International, 2012, 47: 144–149.
FAN M B, HUANG P J, YE B, et al. Analytical modeling for transient probe response in pulsed eddy current testing [J]. NDT & E International, 2009, 42: 376–383.
HUANG C, WU X J, XU Z Y, et al. Pulsed eddy current signal processing method for signal denoising in ferromagnetic plate testing [J]. NDT & E International, 2010, 43: 648–653.
RENINGER P A, MARTELET G, DEPARIS J, et al. Singular value decomposition as a denoising tool for airborne time domain electromagnetic data [J]. Journal of Applied Geophysics, 2011, 75: 264–276.
RAJWADE A, RANGARAJAN A, BANERJEE A. Image denoising using the higher order singular value decomposition [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(4): 849–862.
ZHAO X Z, YE B Y. Similarity of signal processing effect between Hankel matrix based SVD and wavelet transform and its mechanism analysis [J]. Mechanical Systems and Signal Processing, 2009, 23: 1062–1075.
ZHANG L Z. Surface defects inspection for continuous casting slab by pulsed eddy current [D]. Chongqing, China: College of Material Science and Engineering, Chongqing University, 2011 (in Chinese).
HASSANPOUR H, ZEHTABIAN A, SADATI S J. Time domain signal enhancement based on an optimized singular vector denoising algorithm [J]. Digital Signal Processing, 2012, 22: 786–794.
SHIH Y T, CHIEN C S, CHUANG C Y. An adaptive parameterized block based singular value decomposition for image denoising and compression [J]. Applied Mathematics and Computation, 2012, 218: 10370–10385.
LAGO-FERNÁNDEZ L F, SÁNCHEZMONTA Ñ ÉS M, CORBACHO F. The effect of low number of points in clustering validation via the negentropy increment [J]. Neurocomputing, 2011, 74: 2657–2664.
TIAN G Y, HE Y Z, ABEWALE I, et al. Research on spectral response of pulsed eddy current and NDE applications [J]. Sensors and Actuators A, 2013, 189: 313–320.
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Foundation item: the Twelve-Five Pre-Research Project (No. 51325010602)
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Zhu, H., Wang, C., Chen, H. et al. Pulsed eddy current signal denoising based on singular value decomposition. J. Shanghai Jiaotong Univ. (Sci.) 21, 121–128 (2016). https://doi.org/10.1007/s12204-015-1691-y
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DOI: https://doi.org/10.1007/s12204-015-1691-y