A Passive Detection Method of Gas Cloud Concentration Distributions for Leaking Alkane Gas

Methane is the primary component of natural gas. The accurate detection of methane leakage points and concentration is crucial to ensuring safety and environmental protection. However, traditional active gas concentration detection methods are susceptible to interference from dynamic backgrounds, which makes concentration detection challenging. This paper presents a passive method for detecting gas cloud concentration distributions based on a self-developed passive infrared imaging system operating in the 3.2–3.4 μm wavelength band. A methane detection model considering multiple influencing factors was established. During the model development, an adaptive factor was incorporated into the prediction and tracking framework of the Kalman filter to mitigate the effect of time-varying light sources on gas concentration detection performance. Experimental results demonstrate that the detection limit is 0.79%, and the relative error is less than 1.00%. The system enables real-time methane concentration detection and validates its potential for natural gas leakage detection through its industrial application in complex environments. The field test videos and the core code of the proposed method have been made publicly available at: https://github.com/1996Eric/AT-EKF.