Research on Visualization Diagnostic Techniques for the Temperature Field of Laminar Diffusion Flames

<jats:p>To address the challenges of CCD sensor saturation and image noise interference in the non-contact temperature measurement of laminar diffusion flames, this paper proposes a visualization diagnostic technique based on digital image processing. Utilizing the MATLAB toolbox, RGB images were converted into temperature matrices based on the principle of two-color pyrometry, and intuitive two-dimensional temperature contours were generated using pseudo-color transformation. Charge saturation caused by high light intensity was corrected by adjusting the lens aperture. Furthermore, a combined algorithm integrating median filtering, Gaussian filtering, and Laplacian sharpening was employed for image denoising and enhancement. Experimental results demonstrate that aperture adjustment effectively extended the upper temperature limit to approximately 1450 K, while the combined filtering approach significantly improved imaging quality. A two-dimensional numerical simulation was established, revealing that the experimentally calculated temperature distribution patterns were highly consistent with the simulation results. This study validates that the proposed method can accurately and effectively reconstruct the two-dimensional temperature field distribution of laminar diffusion flames.</jats:p>