针对傅里叶变换红外光谱仪检测污染气体时红外光谱信号出现的基线漂移现象,提出一种采用改进迭代多项式拟合的红外光谱基线校正方法,该方法可以自动识别光谱信号的特征峰,从光谱中截断完整的特征峰后,采用双边阈值对红外光谱迭代得到最优的拟合基线。利用仿真光谱以及三氯乙烷、氨气的实测光谱对该方法进行验证,并将其与常见的3种多项式拟合方法进行对比,结果表明:采用所提方法对光谱进行校正后,特征峰更明显,基线更平缓。仿真和实测数据表明,所提方法提高了现有多项式拟合基线校正方法的准确性,是一种具有良好性能的基线校正方法。

The baseline of an infrared spectrum will drift when a Fourier transform infrared spectrometer is used to detect pollution gases. An infrared spectral baseline correction method based on improved iterative polynomial fitting is proposed in this paper. The method automatically identifies characteristic spectral peaks and subsequently cuts off the characteristic peaks from the spectrum. Then, it uses the bilateral threshold to iteratively fit the infrared spectrum to obtain the best-fitting baseline. The proposed method was verified using the simulated and measured spectra of trichloroethane and ammonia, and the results were compared with those obtained by the three common polynomial fitting methods. The results show that the characteristic peaks of the corrected spectra are more obvious and the baseline is more gradual after baseline correction using proposed method. The simulation and measured data show that our baseline correction method improves the accuracy of the existing polynomial fitting baseline correction method and exhibits good performance.