傅里叶变换红外光谱自适应数字滤波算法研究

Research of adaptive digital filtering algorithm for Fourier transform infrared spectroscopy

针对傅里叶变换红外(FTIR)光谱仪在不同类型环境噪声下导致的仪器性能下降的问题,提出了一种根据不同环境噪声实时更新滤波参数的自适应滤波算法。对该算法的基本原理和实现过程进行了理论推导,分析了不同滤波参数设置下的滤波效果,进而利用设计的滤波算法对实测光谱数据进行了滤波处理,对比分析了不同滤波方法下的光谱信噪比(SNR)。研究结果表明:基于巴特沃斯滤波的自适应FTIR光谱滤波方法在2100~2200 cm^(-1)和2500~2600 cm^(-1)波段的SNR较传统硬件滤波分别提高了1.29倍和1.13倍,表明该算法可以有效提升FTIR光谱信噪比,改善FTIR仪器的性能指标。

To address the issue of instrument performance degradation of Fourier transform infrared(FTIR)spectrometers caused by different types of environmental signal noise,an adaptive filtering algorithm,which can update filtering parameters in real-time based on different environmental noise levels,is proposed in this work.The basic principle and implementation process of the algorithm are theoretically deduced,and the filtering effect under different filtering parameters is analyzed.Then,the proposed filtering algorithm is used to filter the measured spectral data,and the spectral signal-to-noise ratio(SNR)of different filtering methods is compared and analyzed.The results show that the SNRs of the adaptive filtering algorithm in 2100-2200 cm^(-1) and 2500-2600 cm^(-1) bands are 1.29 times and 1.13 times those of the traditional hardware filtering,respectively,indicating that the adaptive filtering algorithm proposed can effectively improve SNR of FTIR spectrum and the performance index of FTIR instrument.