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L. Zhu, Y. Zhu, M. Mao and M. Gu, “A New Method for Sparse Signal Denoising Based on Compressed Sensing, Second International Symposium on Knowledge Acquisition and Modeling,” Second International Symposium on Knowledge Acquisition and Modeling, Wuhan, 30 November-1 December 2009, pp. 35-38.

has been cited by the following article:

• TITLE: Modelling and Wavelet-Based Identification of 3-DOF Vehicle Suspension System

  AUTHORS: Khaled Nouri, Hichem Loussifi, Naceur Benhadj Braiek

  KEYWORDS: Suspension System, Discrete and Continuous Wavelet Transform, Signal Denoising, Modal Identification

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.4 No.12, December 5, 2011

  ABSTRACT: In this paper, a three Degrees Of Freedom (DOF) model of a quarter vehicle suspension system is proposed including the seat driver mass. The modal parameters of this system, which indicate the comfort and the safety of the suspension, are identified using Wavelet analysis. Two applications of wavelet analysis are presented: signal denoising based on the Discrete Wavelet Transform (DWT) and modal identification based on the Continuous Wavelet Transform (CWT). It is shown that the CWT analysis of the system response, initially denoised using DWT, allows the estimation of the natural pulsations and the damping ratios. The usefulness of the DWT in denoising and the accuracy of the CWT in modal identification are tested and confirmed by applying them to the proposed model. The complete modeling and identification of a 3-DOF vehicle suspension system is developed and the simulation results verify these statements and are satisfactory.