Use of high dynamic range imaging for quantitative combustion diagnostics.

Abstract

High dynamic range (HDR) imaging is applied to quantitative combustion diagnostics in coflow laminar diffusion flames as a way to improve the signal-to-noise ratio (SNR) and measurement sensitivity. The technique relies on the combination of partially saturated frames into a single unsaturated image; in this work, the effectiveness of the HDR approach is demonstrated when applied to two-color ratio pyrometry. Specifically, it is shown than an increase in SNR results in more precise temperature measurements for both soot and thin filament pyrometry. Linearity and reciprocity analysis under partially saturated conditions were performed on three selected detectors, and the camera response functions, which are required for HDR image reconstruction, were determined. The linearity/reciprocity of the detectors allowed the use of a simplified algorithm that was implemented to compute the HDR images; soot and flame temperature were calculated from those images by employing color-ratio pyrometry. The reciprocity analysis revealed that pixel cross talk can be a limiting factor in a detector's HDR capabilities. The comparison with low dynamic range results showed the advantage of the HDR approach. Due to the higher SNR, the measured temperature exhibits a smoother distribution, and the range is extended to lower temperature regions, where the pyrometry technique starts to lose sensitivity due to detector limitations.