Diode laser absorption tomography using data compression techniques

Chad Lindstrom; Chung-Jen Tam; Ryan Givens; Doug Davis; Skip Williams

doi:10.1117/12.766323

26 February 2008 Diode laser absorption tomography using data compression techniques

Chad Lindstrom, Chung-Jen Tam, Ryan Givens, Doug Davis, Skip Williams

Proceedings Volume 6814, Computational Imaging VI; 68140W (2008) https://doi.org/10.1117/12.766323
Event: Electronic Imaging, 2008, San Jose, California, United States

Abstract

Tunable diode laser absorption spectroscopy (TDLAS) shows promise for in situ monitoring in high-speed flows. However, the dynamic nature of typical flows of supersonic combustors, gas turbine engines and augmenters can also lead to inhomogenities that cannot be captured by a single line-of-sight TDLAS measurement. Instead, multiple measurements varied over several spatial locations need to be made. In the current study, shock train structure in the isolator section of the Research Cell 18 supersonic combustion facility at Wright-Patterson AFB is measured. Although only two view angles are available for measurement, multiple absorption features along with a priori computational fluid dynamics (CFD) simulations enable estimates of two dimensional flow features to be formed. Vector quantization/kmeans data clustering is used to identify key flow features from the temporal history of the raw sinograms. Through the use of multiple absorption features that are measured nearly simultaneously, an approximate two-dimensional image can be formed. This image can be further refined through the use of an optimal set of basis functions that can be derived from a set of CFD simulations that describes the flow shapes.

Citation Download Citation

Chad Lindstrom, Chung-Jen Tam, Ryan Givens, Doug Davis, and Skip Williams "Diode laser absorption tomography using data compression techniques", Proc. SPIE 6814, Computational Imaging VI, 68140W (26 February 2008); https://doi.org/10.1117/12.766323

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