光学学报, 2019, 39 (9): 0930006, 网络出版: 2019-09-09   

用于近红外宽带腔增强吸收光谱的小波去噪 下载: 1159次

Wavelet Denoising in Near-Infrared Broadband Cavity-Enhanced Absorption Spectroscopy
作者单位
1 吉林大学集成光电子学国家重点联合实验室,电子科学与工程学院, 吉林 长春 130012
2 吉林省红外气体传感技术工程研究中心, 吉林 长春 130012
摘要
为了有效抑制检测系统的噪声,提高气体浓度的反演精度,研究了近红外宽带腔增强气体传感系统的小波去噪方法。小波去噪方法的优化分析结果表明,选择db2小波函数作为小波基对含噪信号进行6级分层处理,并选择heursure阈值估计方法,采用局部阈值方式对噪声部分小波系数进行置零处理,可达到最优去噪效果。将近红外宽带腔增强吸收光谱技术与高分辨率傅里叶变换红外光谱仪相结合,建立了用于甲烷检测的气体传感系统,使用最小二乘拟合算法对去噪前后的甲烷吸收系数进行反演。结果表明,采用小波去噪后,反演浓度更接近真实值,反演精度提高7%,信噪比提高90%,系统检测下限降低45%,证明小波去噪算法可以有效提高系统的检测精度。
Abstract
In order to effectively suppress the noise in gas detection and improve the inversion precision of gas concentration, we investigate a wavelet denoising algorithm for near-infrared broadband cavity-enhanced gas sensing system. Optimization analysis of wavelet denoising shows that it can achieve the optimal denoising effect by using db2 wavelet function as the wavelet base to perform 6-layer denoising on the polluted signal, and at the same time, by using heursure threshold estimation method and local threshold to zero the noise part wavelet coefficient. The near-infrared broadband cavity-enhanced absorption spectroscopy technique combined with a high-resolution Fourier transform infrared spectrometer is used to establish a gas sensing system for methane detection. The concentration inversion of methane absorption coefficient before and after wavelet denoising is performed using a least square fitting algorithm. Experimental results show that the inversed concentration results with wavelet denoising are closer to the true value than those without denoising. The inversion accuracy is improved by 7%, the signal-to-noise ratio is increased by 90%, and the system detection limit is reduced by 45%. It is evidenced that the wavelet denoising algorithm can effectively improve the detection accuracy.

姚丹, 郑凯元, 刘梓迪, 李俊豪, 郑传涛, 王一丁. 用于近红外宽带腔增强吸收光谱的小波去噪[J]. 光学学报, 2019, 39(9): 0930006. Dan Yao, Kaiyuan Zheng, Zidi Liu, Junhao Li, Chuantao Zheng, Yiding Wang. Wavelet Denoising in Near-Infrared Broadband Cavity-Enhanced Absorption Spectroscopy[J]. Acta Optica Sinica, 2019, 39(9): 0930006.

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