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.
ZHU Hongyun (朱红运), WANG Changlong* (王长龙), CHEN Hailong (陈海龙), WANG Jianbin (王建斌)
. Pulsed Eddy Current Signal Denoising Based on Singular Value Decomposition[J]. Journal of Shanghai Jiaotong University(Science), 2016
, 21(1)
: 121
-128
.
DOI: 10.1007/s12204-015-1691-y
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