Mr. Meirong Wang Profile

Meirong Wang

at Beijing Institute of Technology

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Proceedings Article | 18 May 2012 Paper

Gas imaging detectivity model combining leakage spot size and range

Jiakun Li, Lingxue Wang, Meirong Wang, Yue Gao, Weiqi Jin

Proceedings Volume 8354, 835415 (2012) https://doi.org/10.1117/12.920664

KEYWORDS: Thermography, Atmospheric modeling, Clouds, Sensors, Imaging systems, Thermal modeling, Signal to noise ratio, Standoff detection, Black bodies, Solar radiation models

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As to visualize the leaking gas cloud which is not visible to the naked eyes, three categories of techniques have emerged, Backscatter Absorption Gas Imaging, Passive Thermal Imaging, and Imaging Spectrometer. Among these systems, Signal to Noise Ratio (SNR) is generally used to deduce gas leakage detection limit and leads to several performance evaluation parameters, such as Noise-Equivalent Spectral Radiance and Noise-Equivalent Concentration-Path Length. However, in most cases, measuring the SNR accurately is not accessible and usually needs auxiliary instruments. Therefore, we focus on researching a gas leakage detection model according to the general parameter of a thermal imager, Noise Equivalent Temperature Difference (NETD). Firstly, the Gas Equivalent Blackbody Temperature Difference (GEBTD) is obtained by calculating the attenuated radiation of the On-plume path and that of the Off-plume path respectively. A simplified form of GEBTD was derived by our previous paper, assuming that the work range was short and the affection of atmospheric transmission was omitted. But in this paper, more factors are considered to establish a more realistic and accurate detectivity model. The radiation of the gas cloud and the attenuation of the atmosphere are taken into account as well as the size of the leakage spot which inevitably affects the concentration path length. Secondly, the NETD and the GEBTD are compared to determine the detection capability. At last, an experiment is designed to verify the accuracy and reliability of this model on the basis of the gas cloud concentration cone distribution model.

Proceedings Article | 18 May 2012 Paper

Spatial concentration distribution model for short-range continuous gas leakage of small amount

Meirong Wang, Lingxue Wang, Jiakun Li, Yunting Long, Yue Gao

Proceedings Volume 8354, 835414 (2012) https://doi.org/10.1117/12.920569

KEYWORDS: Data modeling, Diffusion, Imaging systems, Sensors, Infrared imaging, 3D modeling, Infrared radiation, Thermal modeling, Atmospheric modeling, Systems modeling

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Passive infrared gas imaging systems have been utilized in the equipment leak detection and repair in chemical manufacturers and petroleum refineries. The detection performance mainly relates to the sensitivity of infrared detector, optical depth of gas, atmospheric transmission, wind speed, and so on. Based on our knowledge, the spatial concentration distribution of continuously leaking gas plays an important part in leak detection. Several computational model of gas diffusion were proposed by researchers, such as Gaussian model, BM model, Sutton model and FEM3 model. But these models focus on calculating a large scale gas concentration distribution for a great amount of gas leaks above over 100- meter height, and not applicable to assess detection limit of a gas imaging system in short range. In this paper, a wind tunnel experiment is designed. Under different leaking rate and wind speed, concentration in different spatial positions is measured by portable gas detectors. Through analyzing the experimental data, the two parameters σ_y(x) and σ_z (x) that determine the plume dispersion in Gaussian model are adjusted to produce the best curve fit to the gas concentration data. Then a concentration distribution model for small mount gas leakage in short range is established. Various gases, ethylene and methane are used to testify this model.

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