Chemical Gas Telemetry System Based on Multispectral Infrared Imaging

Li, Kun; Duan, Shaoli; Pang, Lingling; Li, Weilai; Yang, Zhixiong; Hu, Yaohang; Chen, Yu

doi:10.3390/toxics11010083

Cited by 9 publications

(4 citation statements)

References 15 publications

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“…Country: American) [13]. Meanwhile, many researchers have developed multispectral infrared imaging systems based on filtering wheels, which monitor various harmful gases in the atmosphere [14][15][16]. However, most existing infrared detection systems are equipped with only one filter to detect SF6 gas.…”

Section: Conceptual Design Of the Cbi Systemmentioning

confidence: 99%

“…The most representative product is the GF306 gas imaging instrument developed by the American FLIR company (Manufacturer: FLIR Systems, Inc. City: Wilsonville, State abbreviation: OR, Country: USA) [13]. Meanwhile, many researchers have developed multispectral infrared imaging systems based on filtering wheels, which monitor various harmful gases in the atmosphere [14][15][16]. However, most existing infrared detection systems are equipped with only one filter to detect SF 6 gas.…”

Section: Introductionmentioning

confidence: 99%

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Monitoring SF6 Gas Leakage Based on a Customized Binocular System

Si,

Zhao,

Wang

et al. 2024

Sensors

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Sulfur hexafluoride (SF6) gas is extensively utilized as an insulating and arc-quenching medium in the circuit breakers and isolating switches of electrical equipment. It effectively isolates the circuits from the atmosphere and promptly extinguishes arcs. Therefore, the issue of SF6 gas leakage poses a significant threat to the related application fields, and the detection of SF6 gas leakage becomes extremely important. Infrared imaging detection offers advantages including non-contact, high precision, and visualization. However, most existing infrared detection systems are equipped with only one filter to detect SF6 gas. The images captured contain background noise and system noise, making these systems vulnerable to interference from such noises. To address these issues, we propose a method for monitoring SF6 gas leakage based on a customized binocular imaging (CBI) system. The CBI system has two filters, greatly reducing the interference of system noise and background noise. The first filter features the absorption resonant peak of SF6 gas. The second filter is used to record background noise and system noise. One aspect to note is that, in order to avoid the interference of other gases, the central wavelength of this second filter should keep away from the absorption resonant peaks of those gases. Accordingly, the central wavelengths of our customized filters were determined as 10,630 nm and 8370 nm, respectively. Then, two cameras of the same type were separately assembled with a customized filter, and the CBI prototype was accomplished. Finally, we utilized the difference method using two infrared images captured by the CBI system, to monitor the SF6 gas leakage. The results demonstrate that our developed system achieves a high accuracy of over 99.8% in detecting SF6 gas. Furthermore, the CBI system supports a plug-and-play customization to detect various gases for different scenarios.

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Section: Conceptual Design Of the Cbi Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Monitoring SF6 Gas Leakage Based on a Customized Binocular System

Si,

Zhao,

Wang

et al. 2024

Sensors

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“…Invisible infrared radiation is emitted as a result of the temperature of the outer tank, with its wavelength surpassing the range of visible light. The temperature distribution of a target item can be inferred by measuring the power of infrared radiation on its surface, in accordance with the Stefan-Boltzmann law [26,27].…”

Section: Crack Imaging Principle Of Infrared Thermal Cameramentioning

confidence: 99%

Intelligent Extraction of Surface Cracks on LNG Outer Tanks Based on Close-Range Image Point Clouds and Infrared Imagery

Guo,

Zhu,

Zhao

et al. 2023

Preprint

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The precise detection and ongoing surveillance of surface fractures on exterior LNG storage tanks are crucial in guaranteeing the secure transit and storage of natural gas. Undetected fractures have the potential to result in the release of liquefied natural gas (LNG), hence presenting a significant risk to both public health and the environment. This paper presents a novel approach for crack identification, which involves the integration of thermal infrared pictures and point clouds derived from close-range images captured by unmanned aerial vehicles (UAV). The aim of this approach is to overcome the limitations of conventional manual detection methods, namely in terms of efficiency and safety concerns. The primary approach for acquiring two-dimensional photographs of the tank surface is the utilization of infrared technology to generate an infrared dataset capturing the presence of fractures on the storage tanks' exterior. The utilization of the attention mechanism convolutional neural network is employed during the process of model training. The UAV close-range photos were utilized in close-range photogrammetry to generate an accurate point cloud model. This was achieved by incorporating control point coordinates and matching feature points. The infrared photos that were discovered were subsequently matched with this particular model. The 3D model that was officially was employed as a point of reference on the unfolded 2D plane. To construct the depth image, a least-squares approach of least-column fitting was utilized. In order to validate the accuracy of the automated extraction process, a manual crack extraction was conducted on the original close-range image point cloud of the tank exterior. The results indicated that the extracted cracks exhibited an accuracy level of around 97.6%. The experimental findings demonstrate that the process of crack extraction exhibits a high level of accuracy, hence presenting numerous possible applications in the realms of maintenance management and intelligent monitoring. The utilization of this technology is appropriate for the purpose of monitoring the thermal conditions and structural soundness of LNG storage tanks.

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“…Compared with the active method, passive infrared gas imaging detection technology has the advantages of simple structure, more types of detectable gases, no active light source, etc. However, it requires a temperature difference between the measured gas and the background and a low signal-to-noise ratio, making it suitable for gas detection under harsh environments and background temperature differences [15][16][17][18][19][20]. Currently, passive infrared gas imaging detection technology can be divided into hyperspectral imaging technology and multispectral imaging technology according to the number of detection bands.…”

Section: Introductionmentioning

confidence: 99%

Dual-Channel Mapping–Gas Column Concentration Inversion Method Based on Multispectral Imaging

Shi,

Zhao,

Zhao

et al. 2024

Applied Sciences

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Infrared multispectral imaging technology can achieve the long-distance, wide-ranging and fast detection of target gas, and has been widely used in the fields of dangerous-gas detection and environmental monitoring. However, due to the difficulty in acquiring background radiation as well as atmospheric disturbance and noise interference in the detection process, the quantitative detection of gas concentration has become a difficult problem to solve. Therefore, this paper proposes an inversion method for gas column concentration based on infrared multispectral imaging technology. Firstly, infrared background radiation images of the non-target gas absorption spectrum band were collected and converted into background radiation images of the target gas absorption spectrum band according to the dual-channel mapping relationship. Then, combined with the gas radiation images of the target gas absorption spectrum band, the column concentration distribution of the gas was obtained by using the measured calibration relationship between absorbance and column concentration. Experiments of gas detection in different environments were carried out, and the column concentration distribution of the target gas was inverted using this method; the results showed that the average relative error of the inversion of the gas column concentration was 4.84%, which enables the quantitative detection of gas column concentration in a complex environment.

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Chemical Gas Telemetry System Based on Multispectral Infrared Imaging

Cited by 9 publications

References 15 publications

Monitoring SF6 Gas Leakage Based on a Customized Binocular System

Monitoring SF6 Gas Leakage Based on a Customized Binocular System

Intelligent Extraction of Surface Cracks on LNG Outer Tanks Based on Close-Range Image Point Clouds and Infrared Imagery

Dual-Channel Mapping–Gas Column Concentration Inversion Method Based on Multispectral Imaging

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