Denoising Method Based on Sparse Representation for WFT Signal. (13th February 2014)

• Record Type: Journal Article
• Authors: Chen, Xu; Lin, Guoyu; Zhang, Yuxin
• Other Names: Vergara Alexander Academic Editor.
• Is Part Of: Journal of sensors. Volume 2014(2014)
• Publication Date: 2014-02-13
• Subjects: Detectors -- Periodicals; 681.205
• DOI: 10.1155/2014/145870
• Languages: English
• ISSNs: 1687-725X

Abstract

Abstract : 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.