We proposed and demonstrated a wavelet transform modulus maxima （WTMM） de-noising method to decrease the temperature error. In this scheme, the composition scale was determined simply by the WTMM amplitude variation...We proposed and demonstrated a wavelet transform modulus maxima （WTMM） de-noising method to decrease the temperature error. In this scheme, the composition scale was determined simply by the WTMM amplitude variation with the growth of the decomposition scale at 30 ℃, and the signal WTMM was obtained by the wavelet decomposition modulus on every decomposition scale based on the modulus propagating difference between the signal and noise. Then, we reconstructed the signal using the signal WTMM. Experimental results show that the proposed method is effective for de-noising, allowing for a temperature error decrease of about 1 ℃ at 40 ℃ and 50℃ comparing to the original data.展开更多
基金This work was supported by the Natural Science Foundation of China （60977058 ＆ 61307101）, Independent Innovation Foundation of Shandong University （IIFSDU2012JC015） and the key technology projects of Shandong Province （2010GGX10137）.
文摘We proposed and demonstrated a wavelet transform modulus maxima （WTMM） de-noising method to decrease the temperature error. In this scheme, the composition scale was determined simply by the WTMM amplitude variation with the growth of the decomposition scale at 30 ℃, and the signal WTMM was obtained by the wavelet decomposition modulus on every decomposition scale based on the modulus propagating difference between the signal and noise. Then, we reconstructed the signal using the signal WTMM. Experimental results show that the proposed method is effective for de-noising, allowing for a temperature error decrease of about 1 ℃ at 40 ℃ and 50℃ comparing to the original data.
