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Denoising method based on sparse representation for WFT signal

journal contribution
posted on 2022-10-30, 22:06 authored by X Chen, G Lin, Yuxin ZhangYuxin Zhang
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.

History

Journal

Journal of Sensors

Volume

2014

Article number

ARTN 145870

ISSN

1687-725X

eISSN

1687-7268

Language

English

Publication classification

C1.1 Refereed article in a scholarly journal

Publisher

HINDAWI LTD