Image Processing and Edge Detection Techniques to Quantify Shock Wave Dynamics Experiments
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RESEARCH PAPER
Image Processing and Edge Detection Techniques to Quantify Shock Wave Dynamics Experiments L. Zheng1 · B. Lawlor1 · B.J. Katko2 · C. McGuire1 · J. Zanteson2 · V. Eliasson2,3 Received: 30 April 2020 / Accepted: 2 November 2020 © The Society for Experimental Mechanics, Inc 2020
Abstract Experimental studies of multiple shock wave interaction to study transition from regular to irregular reflection rely on the processing of a large amount of schlieren photographs. Here we present an automated algorithm to track individual shock fronts and triple points. First, correction to any optical distortions is applied to the photographs. Next, noise removal and edge detection algorithms are implemented to extract the pixel locations of the shocks. The edge detection algorithm takes advantage of the light intensity feature of the shock waves to distinguish shock fronts from background noise. This algorithm is also capable of separating entangled shock fronts through pattern recognition, which utilizes a discretization method to reduce complex shock geometries to localized linear patterns. Collectively, the algorithms can track shock wave characteristics to sub-pixel precision. This algorithm has been deployed for post processing of shock wave experiments to extract shock wave characteristics including positions and propagation velocities of shock fronts, vertical and horizontal velocities of Mach stems, and triple point trajectories during shock-shock interactions. Results show that the algorithm can process large volumes of data with minimal manual operations, making image processing more precise, efficient and productive while allowing for tracking of Mach stems and triple points. Keywords Shock wave dynamics · Image-processing · Schlieren · Exploding wire
Introduction Experimental investigations of shock wave reflection phenomena are often used to qualitatively validate results from numerical simulations through schlieren photography. However, as advancements in ultra high-speed photography make video recordings of shock dynamic events possible, quantitative information from large volumes of consecutive
This study was partially supported by the US Air Force Research Laboratory under grant No. FA8651-17-1-004 and the National Science Foundation under grant number CBET-1803592. V. Eliasson
[email protected] 1
Department of Mechanical and Aerospace Engineering, University of California, San Diego, La Jolla, CA 92093-0411, USA
2
Department of Structural Engineering, University of California, San Diego, La Jolla, CA 92093-0085, USA
3
Mechanical Engineering Department, Colorado School of Mines, Golden, CO 80401, USA
schlieren photographs becomes desirable. Under such context, computer aided image processing techniques that are capable of efficiently and reliably tracking the positions of shock fronts become critical for avoiding repetitive manual work during post processing. Especially, in the study of regular to irregular shock wave transition phenomena, experimental images often consist of multiple de
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