论文部分内容阅读
为改善可调谐二极管激光吸收光谱(TDLAS)系统的检测性能,以浓度为50×10-6和17×10-6的H2S气体检测为例,根据TDLAS系统的噪声特征,选择了4种数字滤波技术并利用Visual C++软件分别编写了程序对二次谐波原始信号进行压噪和有效信号的提取。结果表明,采用非线性最小二乘法与数字平均滤波技术相结合,使系统理论检测极限由原来的30×10-6提高到了5×10-6量级;对于反演后气体的浓度信号则采用Kalman滤波进行再去噪,使信噪比提高了近8倍。比较结果表明,经过上述滤波处理,TDLAS系统的信噪比和检测极限性能有明显改善。本文的上述方法实际应用到我们的TDLAS在线工业排放气体的测量系统中,取得了良好的效果。
In order to improve the detection performance of tunable diode laser absorption spectroscopy (TDLAS) system, taking the detection of H2S gas with concentration of 50 × 10-6 and 17 × 10-6 as an example, four kinds of digital filtering are selected according to the noise characteristics of TDLAS system Technology and the use of Visual C + + software were prepared procedures for the second harmonic original signal noise and effective signal extraction. The results show that using the combination of nonlinear least square method and digital average filtering technique, the detection limit of system theory is increased from 30 × 10-6 to 5 × 10-6. For the gas concentration signal after inversion, Kalman filtering to re-noise, the signal to noise ratio increased by nearly 8 times. The comparison results show that the signal-to-noise ratio and detection limit performance of TDLAS system have been significantly improved after the above filtering process. The above method of this article is actually applied to our TDLAS online industrial exhaust gas measurement system, and achieved good results.