| 光谱学与光谱分析 |
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| MAX-DOAS Tomography Reconstruction for Gas Plume |
| WEI Min-hong1, 2, TONG Min-ming1, LI Su-wen2*, XIAO Jian-yu2 |
1. School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, China
2. School of Physics and Electronic Information, Huaibei Normal University, Huaibei 235000, China |
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Abstract In order to achieve precisely two-dimensional spatial distribution reconstruction of smoke plume, passive MAX-DOAS tomography is established, the measurement of the spatial distribution of the exhaust plume is implemented by more passive multi-axis differential absorption spectrum system. First, the multi-axis differential absorption spectrum system and its mechanism of inverse gas concentration are introduced in the paper. Then, algebra iterative algorithm is adopted to extract the information of the trace gas concentration in reconstruction simulation with different models and different scanning optical path, and the reconstruction program is designed. Then, the numerical simulation results are compared. Finally, a platform of multi-axis differential absorption optical tomography system is set up, a field campaign was carried out. The numerical simulation results show that the MAX-DOAS tomography can accurately reconstruct two-dimensional spatial distribution of plume model, the reconstruction error of MAX-DOAS tomography with four light sources is about a third of the reconstruction error with double light sources, moreover, the reconstruction time is about a quarter of the reconstruction time of double light sources, and the reconstruction error of the twin peaks model is greater than that of the one peak model. Field test results show that the integral data of reconstruction image is consistent with the measured projection data of multi-axis differential absorption spectrum, the spatial distribution reconstruction of plume is in line with the actual situation. Studies have shown that the result of numerical simulation and field test results have consistency.
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Received: 2014-11-05
Accepted: 2015-02-06
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Corresponding Authors:
LI Su-wen
E-mail: 57689864@qq.com
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