Low-Contrast High-Speed Video Analysis for Rotating Detonation Rocket Engines

Low-contrast high-speed video from rotating detonation rocket engines makes analyzing the detonation wave dynamics difficult. This paper outlines a method to process raw video frames into a filtered time series of brightness measured around a discretized one-dimensional annulus, enabling a frequency-domain extraction of wave frequency and wave number. For low-contrast videos in which the combustion chamber boundaries are not readily detected, an alternative approach uses a full-video singular value decomposition (SVD) followed by a manual selection of the annular region. In addition, a Riemannian gradient descent algorithm for SVD computation is investigated, offering the potential for faster convergence under specific conditions. The uncertainty of the frequency analysis procedure is quantified by comparing results against known pressure sensor (PCD) data, demonstrating the robustness and reliability of this method across a range of experimental conditions.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.2514/6.2025-98550
Primary Topic
Combustion and Detonation Processes
Type
article
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article

Low-Contrast High-Speed Video Analysis for Rotating Detonation Rocket Engines

M. R. Gómez
Combustion and Detonation Processes
article

Low-Contrast High-Speed Video Analysis for Rotating Detonation Rocket Engines

M. R. Gómez
article en

Abstract

Low-contrast high-speed video from rotating detonation rocket engines makes analyzing the detonation wave dynamics difficult. This paper outlines a method to process raw video frames into a filtered time series of brightness measured around a discretized one-dimensional annulus, enabling a frequency-domain extraction of wave frequency and wave number. For low-contrast videos in which the combustion chamber boundaries are not readily detected, an alternative approach uses a full-video singular value decomposition (SVD) followed by a manual selection of the annular region. In addition, a Riemannian gradient descent algorithm for SVD computation is investigated, offering the potential for faster convergence under specific conditions. The uncertainty of the frequency analysis procedure is quantified by comparing results against known pressure sensor (PCD) data, demonstrating the robustness and reliability of this method across a range of experimental conditions.

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Combustion and Detonation Processes
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