光谱学与光谱分析, 2016, 36 (9): 2997, 网络出版: 2016-12-26   

基于Gabor变换的TDLAS检测信号的降噪研究

作者单位
1 中国科学院合肥物质科学研究院应用技术研究所, 安徽 合肥 230031
2 中国科学技术大学, 安徽 合肥 230026
3 北京市烟草质量监督检测站, 北京 100029
摘要
可调谐二极管激光吸收光谱(TDLAS)技术结合波长调制光谱(WMS)技术是用于痕量气体检测的重要技术手段。 通过锁相放大器进行谐波检测, 对解调得到的二次谐波信号进行分析可获得气体吸收的信息。 但由于二次谐波信号受到噪声的影响, 降低了检测系统的精度和稳定性。 为了提高TDLAS检测系统的信噪比(SNR), 提出了一种基于Gabor变换对二次谐波信号进行数字滤波降噪的方法。 以CH4在1 653.72 nm处的吸收光谱为例, 通过仿真和实验对该降噪方法的有效性进行了验证。 仿真结果表明, 通过Gabor变换对信噪比为0dB的二次谐波信号进行处理后, 系统的信噪比可提高15.73 dB。 实验结果表明, 基于Gabor变换进行降噪处理后, CH4浓度在0.001%~0.02%区间内与二次谐波峰值的线性相关系数r达到了0.996 59, 且系统的检测精度和稳定性明显提高。
Abstract
Tunable diode laser absorption spectroscopy (TDLAS) technology combined with wavelength modulation spectroscopy (WMS) technology is an important technique for trace gas detection. Detected with the lock-in amplifier, the second harmonic signal obtained after demodulation is analyzed to get the gas absorption information. However, the second harmonic signal is affected by noise which reduces the accuracy and stability of the detection system. To improve the signal to noise ratio (SNR) of the TDLAS detection system, a denoising method based on Gabor transform is proposed for second harmonic signal noise reduction. Taking the CH4 absorption spectrum at 1 653.72 nm as an example, the effectiveness of the noise reduction method is verified through simulation and experiments. The simulation results show that the signal to noise ratio for the second harmonic signal of 0 dB can be improved 15.73 dB with Gabor transform-based denoising method. Experimental results show that with the Gabor transform-based denoising method, the linear correlation coefficient r can be as high as 0.996 59 between the second harmonic peak value and the CH4 concentration in the range of 0.001%~0.02%. At the same time, the detection accuracy and stability of the system have been improved significantly.

崔海滨, 杨柯, 张龙, 吴晓松, 刘勇, 王安, 李慧, 计敏. 基于Gabor变换的TDLAS检测信号的降噪研究[J]. 光谱学与光谱分析, 2016, 36(9): 2997. CUI Hai-bin, YANG Ke, ZHANG Long, WU Xiao-song, LIU Yong, WANG An, LI Hui, JI Min. [J]. Spectroscopy and Spectral Analysis, 2016, 36(9): 2997.

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