为了抑制甲烷传感器中统计特性无法预知的电学噪声, 本文结合递归最小二乘自适应去噪算法和直接吸收光谱技术,使用中心波长为3 291 nm的带间级联激光器和多反射吸收气室, 研制了一种电域自适应中红外甲烷传感器系统。在传统探测器输出信号(称为信号通道)的基础上, 增加了激光器电流驱动器的反馈信号作为噪声通道来感知电学噪声。利用MATLAB软件对最小二乘法在直接吸收光谱技术中的滤波效果进行了仿真。通过在激光器驱动信号中施加不同的噪声,实验验证了最小二乘法的去噪效果。针对该传感器的Allan标准差结果表明, 当不使用自适应最小二乘法时, 系统在积分时间为6 s的检测下限为78.8 nL/L; 使用RLS自适应算法时, 系统的检测下限为43.9 nL/L。相比基于传统传感结构和滤波方法的中红外直接吸收光谱传感器, 本文所报道的中红外甲烷传感器由于采用了电域自适应滤波方法, 因而呈现出更好的抗干扰性和稳定性。

In order to suppress sensor noise with unknown statistical properties in an electrical domain, a novel mid-infrared CH4 sensor was proposed based on a 3 291 nm interband cascade laser and a multipass gas cell. This sensor operates using Recursive Least Square (RLS) self-adaptive denoising algorithm and Direct Laser Absorption Spectroscopy (DLAS) technique. Based on the traditional detector output (called the signal channel), a noise channel was added to generate electrical noise using the feedback signal of the laser driver. Numerical simulation in MATLAB was performed to evaluate the filtering performance of the RLS algorithm in the DLAS application. By adding different noise into the driving signal of the laser, potential denoising and sensing capabilities of the RLS algorithm were experimentally evaluated. Taking into account only the intrinsic noise of the sensor, the Allan deviation indicates a measurement precision of ~78.8 nL/L) with a ~6 s averaging time without using any filter. For comparison, Allan deviation of ~43.9 nL/L was obtained with a ~ 6 s averaging time using self-adaptive filtering. The reported sensor, incorporating the RLS self-adaptive denoising algorithm, demonstrates enhanced noise immunity and sensitivity compared to the mid-infrared DLAS sensor using the traditional sensing architecture and the filtering method.