The Application of Complex Wavelet Transform to Spectral Signals Background Deduction

Abstract

The accuracy of spectrograms may be affected by baseline excursion or drift when infrared spectrometers are used in the analyses of gases. Background deduction or baseline correction is one of the effective pretreatment methods that can improve measurement accuracy. This paper presents a novel methodology based on complex wavelet transform algorithm to perform background deduction. The complex wavelet transform methodology establishes a complex wavelet filter to decompose the spectral signals first, and set the decomposition coefficients in the high-frequency section to zero, and then reconstruct the background signals; finally, the background deduction can be realized by deducting the background signals. In this study, the complex wavelet established by Daubechies was selected to demonstrate background deduction aiming at simulative spectral signals with different backgrounds and the real spectral signal of SF6 decomposition gases. Compared with the results done by the real wavelet transform in the same conditions, the results indicate that complex wavelet transform methodology can perform background deduction more efficiently than real wavelet transform methodology, thus improving the effectiveness and precision of spectrogram measurements greatly, which is useful for SF6 gas decomposition compositions analysis