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数字滤波方法在TDLAS逃逸氨检测中的选用
引用本文:邹得宝,陈文亮,杜振辉,贾浩,齐汝宾,李红莲,甄杨,侯艳霞,徐可欣. 数字滤波方法在TDLAS逃逸氨检测中的选用[J]. 光谱学与光谱分析, 2012, 32(9): 2322-2326. DOI: 10.3964/j.issn.1000-0593(2012)09-2322-05
作者姓名:邹得宝  陈文亮  杜振辉  贾浩  齐汝宾  李红莲  甄杨  侯艳霞  徐可欣
作者单位:1. 天津大学精密测试技术及仪器国家重点实验室,天津 300072
2. 天津大学微光机电系统技术教育部重点实验室,天津 300072
3. 河北大学质量技术监督学院,河北 保定 071002
基金项目:国家重点实验室探索性自主选题,天津市自然科学基金重点项目,河北省自然科学基金项目,河北省高等学校科学技术研究指导项目
摘    要:介绍了可调谐半导体激光吸收光谱技术(TDLAS)原理和实验系统,并对系统噪声进行了分析;以体积比浓度为90×10-6和30×10-6的NH3为例,利用TDLAS系统采集了该浓度气体的二次谐波原始光谱。为改善光谱信号,分别用五种数字滤波方法对原始光谱进行了滤波处理比较,做了NH3的浓度梯度实验并对浓度为20×10-6 NH3进行了长时间监测实验。实验结果表明,算术平均-小波变换滤波相比其他方法更有效地对原始光谱信号进行了改善,提高了系统信噪比和信号平滑度,使系统浓度检测限由原来的10×10-6降低到1.25×10-6,信噪比提高了约14倍,为逃逸氨极低浓度检测提供了一种较为有效的数据预处理方法。

关 键 词:可调谐激光吸收光谱(TDLAS)  逃逸氨检测  噪声分析  数字滤波  小波变换  
收稿时间:2012-03-30

Selection of Digital Filtering in the Escaping Ammonia Monitoring with TDLAS
ZOU De-bao,CHEN Wen-liang,DU Zhen-hui,JIA Hao,QI Ru-bin,LI Hong-lian,ZHEN Yang,HOU Yan-xia,XU Ke-xin. Selection of Digital Filtering in the Escaping Ammonia Monitoring with TDLAS[J]. Spectroscopy and Spectral Analysis, 2012, 32(9): 2322-2326. DOI: 10.3964/j.issn.1000-0593(2012)09-2322-05
Authors:ZOU De-bao  CHEN Wen-liang  DU Zhen-hui  JIA Hao  QI Ru-bin  LI Hong-lian  ZHEN Yang  HOU Yan-xia  XU Ke-xin
Affiliation:1. State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China2. Key Laboratory of Micro-Opto-Electro-Mechanical System Technology,Tianjin University, Ministry of Education, Tianjin 300072, China3. College of Quality & Technical Supervision, Hebei University, Baoding 071002, China
Abstract:Tunable diode laser absorption spectroscopy technology (TDLAS), with its advantages of high selectivity and accuracy, provides a reliable approach to the on-line detection of escaping ammonia. Firstly, the present paper introduces the TDLAS principle, experimental system and the analyses of system noise. Then with the concentration of 90×10-6 and 30×10-6 NH3 for example, we used TDLAS system to collect their second harmonic original spectrum with all kinds of noise interference. To improve the signal spectrum, five types of digital filtering methods were respectively used to filter the original spectrum. Finally we did the NH3 experiments of concentration gradient and the long time monitoring: NH3 experiment of 20×10-6. The analysis indicated that the averaging-wavelet filtering is validated to be more accurate than the other filtering methods in the noise reduction, which can improve the precision of the monitoring system from 10×10-6 to 1.25×10-6 and the SNR also increases by 14 times. It provides an effective pretreatment during the monitoring of escaping ammonia of extremely low concentration.
Keywords:Tunable diode laser absorption spectroscopy(TDLAS)  Escaping Ammonia Monitoring  Noise analysing  Digital filtering  Wavelet   
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