Dynamic Imaging and Inverse Quantification Method of Methane Gas Cloud with Laser Scanning Technology

Existing detection technologies struggle to simultaneously achieve visualization, accurate localization, and quantitative identification of industrial methane microleakages. Herein, we propose a laser scanning-based dynamic imaging and inverse quantification method for methane gas clouds, which integrates tunable diode laser absorption spectroscopy with a two-dimensional pan-tilt unit to realize millisecond-level concentration response and high-precision two-dimensional imaging of methane plumes, with targeted correction of the scanning hysteresis effect. By coupling the path-integrated concentration data obtained via two-dimensional scanning with wind field simulation, we establish a flux-based leakage rate inversion algorithm and identify its optimal applicable interval at 0.2–0.4 m downstream of the leakage source (with a maximum coefficient of determination R2 of 0.9795 at 0.3 m). Systematic experiments and blind tests demonstrate that this method enables obvious quantitative gradient discrimination of industrial methane microleakages at 1–5 L/min, with performance superior to that of conventional detection technologies. This work provides an innovative methodological approach and feasible technical route for the intelligent monitoring and precise emission reduction of industrial methane leakages, laying a foundation for its future engineering applications.