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12 December 2018 Specular reflectance calibration based on integral cavity output spectroscopy
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Proceedings Volume 10846, Optical Sensing and Imaging Technologies and Applications; 108462N (2018) https://doi.org/10.1117/12.2505562
Event: International Symposium on Optoelectronic Technology and Application 2018, 2018, Beijing, China
Abstract
To determine the reflectance of the optical resonator lens, an open optical resonant cavity and a long-path absorption reference cell (absorption length has already known) were build up. The measurement is executed with a spectral line of 13146.58cm-1 in the atmospheric environment. By adjusting the resonator cavity length, the integrated absorbance at different cavity lengths is obtained and compared with the integrated absorbance of the long-path absorption cell to obtain the cavity length gain coefficient. The average value of the gain coefficient measured in the experiment is 85.1782, the standard deviation is 0.420123, and the average reflectivity is calculated as 0.988396, the standard deviation is 0.000056324. To determine the accuracy of the reflectance, we adjusted the cavity length to 17cm, and measured the oxygen absorption spectral signal in the atmospheric environment (@288.5K,1atm).The measured integral absorbance A is 0.0574223(S(δ)=0.000436793), the calculated oxygen component concentration X=20.86%, compared with the value measured by the oxygen concentration meter, the error ∆=0.0031%. The experimental results show that this system can effectively carry out calibration work of cavity mirror reflectivity, at the same time, it also proves that the system has the ability to measure weak-oxygen spectrum absorption signals under short-distance conditions.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaohui Zhu, Wei Rao, Gaoping Fang, Guangyu Wang, and Junling Song "Specular reflectance calibration based on integral cavity output spectroscopy", Proc. SPIE 10846, Optical Sensing and Imaging Technologies and Applications, 108462N (12 December 2018); https://doi.org/10.1117/12.2505562
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