Abstract

This study examines how the wavelet is affected by the wavelet function and thermal parameters by combining radiative and conductive heat transfer with Daubechies discrete wavelet decomposition for signal processing. By comparing time-frequency information under different sampling time interval, we can deduce that the large sampling time interval causes the detail coefficients to focus on the high frequency area. Regarding the wavelet coefficient, the radiation characteristics, heating power, heating time, and actual random errors will affect the wavelet frequency. The thermal conductivity and extinction coefficient have a great influence on the detail coefficient, while the albedo has an impact on the temperature and the amplitude of the wavelet detail coefficient in the range of 0.5-0.9, and the asymmetry factor has a significant effect on the time of the temperature peak. The wavelet detail coefficient of the heating side temperature changes more dramatically than that of the cooling side. The detail coefficient of the low-frequency region is more affected by thermal physical factors whereas the high-frequency portion is more affected by random errors and heating power. This law can improve the accuracy of acquiring physical attributes by filtering out random errors in practical applications.

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