Application of Wavelet Threshold De-noising to Sound Travel-time Estimation

摘要

The key to stored grain temperature measurement by acoustic method is to measure sound travel-time exactly. Grain is a highly absorbing acoustic medium,as a result,the sound signal received by the microphne far from the sound source has very low signal-to-noise ratio. In order to improve the sound travel-time estimation accuracy,a wavelet denoisingbased cross correlation approach (in short CC_WTDN) is proposed. Soft threshold is used for its nice mathematical properties. Four threshold selection rules,that is,VisuShrink estimator,SUREShrink estimator,Heuristic estimator and Minimax estimator are tried. Simulation results based on a acoustic model of grain show that basic coross correlation method (BCC) can work well only when the sound wave path is not longer than 7.07m; while CC_WTDN can give good estimations even if the sound wave path is long as 10m. The four threshold rules tried give similar de-noising effects. The levels of wavelet decomposition have significant influence on de-noising effect.