Remote detection of carbon monoxide by FTIR for simulating field detection in industrial process

Qiankun Gao; Wenqing Liu; Yujun Zhang; Mingguang Gao; Liang Xu; Xiangxian Li; Ling Jin

doi:10.1117/12.2247072

26 October 2016 Remote detection of carbon monoxide by FTIR for simulating field detection in industrial process

Qiankun Gao, Wenqing Liu, Yujun Zhang, Mingguang Gao, Liang Xu, Xiangxian Li, Ling Jin

Author Affiliations +

Proceedings Volume 10156, Hyperspectral Remote Sensing Applications and Environmental Monitoring and Safety Testing Technology; 101561G (2016) https://doi.org/10.1117/12.2247072
Event: International Symposium on Optoelectronic Technology and Application 2016, 2016, Beijing, China

Abstract

In order to monitor carbon monoxide in industrial production, we developed a passive gas radiation measurement system based on Fourier transform infrared spectroscopy and carried out infrared radiation measurement experiment of carbon monoxide detection in simulated industrial production environment by this system. The principle, condition, device and data processing method of the experiment are introduced in this paper. In order to solve the problem of light path jitter in the actual industrial field, we simulated the noise in the industrial environment. We combine the advantages of MATHEMATICA software in the aspects of graph processing and symbolic computation to data processing to improve the signal noise ratio and noise suppression. Based on the HITRAN database, the nonlinear least square fitting method was used to calculate the concentration of the CO spectra before and after the data processing. By comparing the calculated concentration, the data processed by MATHEMATICA is reliable and necessary in the industrial production environment.

Citation Download Citation

Qiankun Gao, Wenqing Liu, Yujun Zhang, Mingguang Gao, Liang Xu, Xiangxian Li, and Ling Jin "Remote detection of carbon monoxide by FTIR for simulating field detection in industrial process", Proc. SPIE 10156, Hyperspectral Remote Sensing Applications and Environmental Monitoring and Safety Testing Technology, 101561G (26 October 2016); https://doi.org/10.1117/12.2247072

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