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Journal of Sensors
Volume 2014, Article ID 145870, 10 pages
Research Article

Denoising Method Based on Sparse Representation for WFT Signal

1School of Information and Control, Nanjing University of Information Science and Technology, Nanjing 210044, China
2School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China

Received 26 October 2013; Revised 2 January 2014; Accepted 9 January 2014; Published 13 February 2014

Academic Editor: Alexander Vergara

Copyright © 2014 Xu Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Affected by external noise and various nature disturbances, Wheel Force Transducer (WFT) signal may be completely submerged, and the sensitivity and the reliability of measurement can be strongly decreased. In this paper, a new wavelet packet denoising method based on sparse representation is proposed to remove the noises from WFT signal. In this method, the problem of recovering the noiseless signal is converted into an optimization problem of recovering the sparsity of their wavelet package coefficients, and the wavelet package coefficients of the noiseless signals can be obtained by the augmented Lagrange optimization method. Then the denoised WFT signal can be reconstructed by wavelet packet reconstruction. The experiments on simulation signal and WFT signal show that the proposed denoising method based on sparse representation is more effective for denoising WFT signal than the soft and hard threshold denoising methods.