Hybrid algorithm for the detection of turbulent flame fronts

Experiments in Fluids, vol. 64, pp. 104

Abstract

Abstract: This paper presents a hybrid and unsupervised approach to flame front detection for low signal-to-noise planar laser-induced fluorescence (PLIF) images. The algorithm combines segmentation and edge detection techniques to achieve low-cost and accurate flame front detection in the presence of noise and variability in the flame structure. The method first uses an adaptive contrast enhancement scheme to improve the quality of the image prior to segmentation. The general shape of the flame front is then highlighted using segmentation, while the edge detection method is used to refine the results and highlight the flame front more accurately. The performance of the algorithm is tested on a dataset of high-speed PLIF images and is shown to achieve high accuracy in finely wrinkled turbulent hydrogen-enriched flames with order of magnitude improvements in computation speed. This new algorithm has potential applications in the experimental study of turbulent flames subject to intense wrinkling and low signal-to-noise ratios. Supplementary Information: The online version contains supplementary material available at 10.1007/s00348-023-03651-6.

Authors 4

1. Oussama Chaib corresponding

   University of Cambridge

   Affiliation as printed

   Trumpington Street, Cambridge, CB2 1PZ UK Department of Engineering, Cambridge University

   Department of Engineering, Cambridge University, Trumpington Street, Cambridge, CB2 1PZ, UK

2. Yutao Zheng corresponding

   University of Cambridge

   Affiliation as printed

   Trumpington Street, Cambridge, CB2 1PZ UK Department of Engineering, Cambridge University

   Department of Engineering, Cambridge University, Trumpington Street, Cambridge, CB2 1PZ, UK

3. Simone Hochgreb corresponding

   University of Cambridge

   Affiliation as printed

   Trumpington Street, Cambridge, CB2 1PZ UK Department of Engineering, Cambridge University

   Department of Engineering, Cambridge University, Trumpington Street, Cambridge, CB2 1PZ, UK

4. Isaac G. Boxx corresponding Aachen Germany Chair of Optical Diagnostics for Energy, Process and Chemical Engineering

   RWTH Aachen University · Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

   Affiliation as printed

   70569 Stuttgart, Germany Institut für Verbrennungstechnik, Deutsches Zentrum für Luft- und Raumfahrt (DLR)

   Aachen, Germany Chair of Optical Diagnostics for Energy, Process and Chemical Engineering, RWTH Aachen University

   Institut für Verbrennungstechnik, Deutsches Zentrum für Luft- und Raumfahrt (DLR), 70569, Stuttgart, Germany