Research on Application of Wavelet Denoising Method Based on Signal to Noise Ratio in the Bench Test

Abstract:

During the tests of the vehicle automatic transmission bench, the acceleration signal is needed to be denoised. As a means of denoising, wavelet threshold denoising method has small amount of calculation and better filtering effect. However, adopting different wavelet basis functions as well as different threshold rules might have a direct effect on the signal denoising. In this paper, we firstly construct the simulated noisy signal approximated to the observed signal, and then do the signal denoising experiment of parameter matching. Secondly, seven Symlets wavelet basis functions and four classical wavelet threshold rules are selected and tested one by one. Signal to noise ratio (SNR) and root mean square error (RMSE) of the denoised signal, the evaluation indicators, are calculated and carried out in accordance with the merits of denoising effect. Thus the optimal combination of the fixed threshold rule and sym8 wavelet basis function is obtained. Finally, this combination is used in the bench test to denoise the angular acceleration signal, and good filtering effect is achieved.

• Periodical: Applied Mechanics and Materials (Volumes 457-458)
• Pages: 1156-1162
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.457-458.1156
• Online since: October 2013
• Authors: Jian Jun Zhong, Sheng Nan Fang, Chang Ying Linghu
• Keywords: Automatic Transmission, Bench, Root Mean Square Error, Signal to Noise Ratio, Threshold Rule, Wavelet Basis Function, Wavelet Denoising

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