Abstract
Sound velocity is dependent on medium temperature and can be estimated from the sound travel-time in medium. Stored grain is a highly absorbing acoustic medium, therefore the acoustic signal distorts seriously after a long distance transmission, which increase the difficulty in the estimation of sound travel-time in stored grain. In order to improve the accuracy of travel-time estimation and hence the accuracy of acoustic temperature measurement under noisy environment, a new method based on basic cross-correlation combined with wavelet transform (for short BCC_WT) is proposed. Using the simulation data calculated by means of grain-acoustic-model, the acoustic travel-times along all the effective sound wave paths in a grain bin with 16 sound sources/receivers isometrically on its periphery were estimated by basic cross-correlation (for short BCC) and BCC_WT, respectively. Simulation results show that for a short sound wave path, both BCC and BCC_WT can give good estimation; for a long path, BCC cannot work while BCC_WT works well.
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