Remote sensing imaging technology is one of the most powerful tools for gas leak monitoring in chemical industrial parks. In the case of leaks, it is necessary to quickly and accurately obtain detailed information of the gas cloud (volume, distribution, diffusion situation and location). This paper proposes a 3-D quantitative reconstruction method for gas clouds. Two scanning Fourier transform infrared (FTIR) remote-sensing imaging systems were used to perform telemetry experiments in a monitored space with a total volume of 314.9 m³, and the released gases were SF₆ and CH₄. One scanning FTIR remote-sensing imaging system can only measure a 2-D concentration-path-length product (CL) image of a 3-D gas cloud, where each pixel has attitude information of elevation and azimuth. Geometric methods are applied to locate the monitored space and construct a 3-D grid (longitude, latitude, altitude). The optical path length (OPL) sparse matrix of each layer is generated, and the concentration distribution of each layer is reconstructed by the simultaneous algebraic reconstruction technique (SART). The reconstructed results of each layer are stacked into a 3-D gas cloud and displayed on the 3-D Earth software at a set threshold. Three-dimensional leaking gas clouds (CH₄, SF₆) with geometric information and concentration distribution has been generated through the above processes from measurement, localization to reconstruction and display. On the premise that the gas cloud is completely covered by the field of view of each scanning system, the localization and quantification of the gas cloud is available. Then weighted concentration centers can be calculated from these gas clouds to approximate the leak source. The proposed method effectively extends the online leak monitoring application of the scanning FTIR remote-sensing imaging system.

Yunyou Hu

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