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用于空间和光谱火焰诊断的压缩感知

Compressive sensing for spatial and spectral flame diagnostics.

作者信息

Starling David J, Ranalli Joseph

机构信息

Division of Science, Penn State University, Hazleton, PA, 18202, USA.

College of Engineering, Penn State University, Hazleton, PA, 18202, USA.

出版信息

Sci Rep. 2018 Feb 7;8(1):2556. doi: 10.1038/s41598-018-20798-z.

Abstract

Combustion research requires the use of state of the art diagnostic tools, including high energy lasers and gated, cooled CCDs. However, these tools may present a cost barrier for laboratories with limited resources. While the cost of high energy lasers and low-noise cameras continues to decline, new imaging technologies are being developed to address both cost and complexity. In this paper, we analyze the use of compressive sensing for flame diagnostics by reconstructing Raman images and calculating mole fractions as a function of radial depth for a highly strained, N-H diffusion flame. We find good agreement with previous results, and discuss the benefits and drawbacks of this technique.

摘要

燃烧研究需要使用最先进的诊断工具,包括高能激光器和门控冷却电荷耦合器件(CCDs)。然而,对于资源有限的实验室来说,这些工具可能会带来成本障碍。虽然高能激光器和低噪声相机的成本持续下降,但仍在开发新的成像技术以解决成本和复杂性问题。在本文中,我们通过重建拉曼图像并计算高度应变的N-H扩散火焰中作为径向深度函数的摩尔分数,分析了压缩传感在火焰诊断中的应用。我们发现与先前的结果吻合良好,并讨论了该技术的优缺点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6493/5803252/cfb9f0d431e8/41598_2018_20798_Fig1_HTML.jpg

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