This paper suggests a new short wave infrared (SWIR)-imaging technique which can overcome these limitations. In addition to a two dimensional (2D) SWIR camera, the system also comprises a 2D visible light camera, an Inertial Measurement Unit (IMU), and global positioning system (GPS) to accurately determine the location of the leak using image correlation and triangulation techniques. The paper also suggests a low cost experimental setup used to assess the performance of the system to accurately quantify and localize CH4 gas leak. An Artificial Neural Network (ANN), was assessed using this setup. Series of extensive experimental tests demonstrate the capability of the system to detect, quantify, and localize CH4 gas leak for different scenarios. The corresponding results reveal that the ANN algorithm yields accurate results for gas mass leak measurement and localization using a SWIR optical filter. Uncertainties of gas mass leak flow measurement did not exceed 2.1% and 3.76% using a SWIR LED source with and without a SWIR filter respectively. This leads to state that the suggested system can be a tangible alternative for next generation leak detection systems.
In oil and gas fields, gas leakage is one of the major concerns, as it causes serious economical, safety, and health consequences. This requires a frequent and periodic inspections of all equipment which either store or transport gases, such as gas pipelines and gas storage tanks. In this paper, a real-time leak detection and localization system which can operate fully autonomously either in a drone or a mobile robot is suggested. The apparatus has the advantage of remotely detecting leaks even in case of humid weather, situation for which most recent leak detection systems such as Long wave Infrared (LWIR) and Medium wave IR (MWIR) fail. The system consists of a Short wave IR (SWIR) camera to remotely detect the existing of leaks even in case of humid weather or during the rain. In addition, the system is not sensitive to thermal radiations which is the case of LWIR and MIIR radiations. A CCD camera, together with a set of sensors that include an Inertial Measurement Unit (IMU) and global positioning system (GPS) are used to accurately determine the location of the leak using image correlation and triangulation techniques. A series of extensive experimental tests demonstrate the capability of the system to detect different types of gas leaks for different scenarios. This leads to state that the suggested system can be a tangible alternative for next generation leak detection systems.
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