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

Area of Science:

• Environmental Science
• Analytical Chemistry
• Optical Engineering

Background:

• Industrial methane microleakages pose significant environmental and safety risks.
• Current detection methods lack simultaneous visualization, localization, and quantification capabilities.
• Accurate monitoring is crucial for effective emission reduction strategies.

Purpose of the Study:

• To develop an advanced method for detecting and quantifying industrial methane microleakages.
• To overcome limitations of existing technologies in visualizing and localizing methane plumes.
• To enable precise emission reduction through intelligent monitoring.

Main Methods:

• A laser scanning approach integrating tunable diode laser absorption spectroscopy (TDLAS) with a 2D pan-tilt unit.
• Real-time 2D imaging of methane plumes with millisecond-level concentration response.
• Correction of scanning hysteresis effects for improved accuracy.
• Development of a flux-based leakage rate inversion algorithm using path-integrated concentration data and wind field simulation.

Main Results:

• Achieved high-precision 2D imaging and millisecond-level concentration response for methane plumes.
• Identified an optimal interval (0.2-0.4 m) for leakage rate inversion with R² up to 0.9795.
• Demonstrated quantitative gradient discrimination of methane microleakages from 1-5 L/min.
• Outperformed conventional detection technologies in systematic experiments and blind tests.

Conclusions:

• The proposed laser scanning method offers a superior approach for detecting industrial methane microleakages.
• This innovative technique provides a feasible route for intelligent monitoring and precise emission reduction.
• The findings lay the groundwork for future engineering applications in methane emission control.