Computer Vision Study of the Flow Generated by a Sliding Discharge

Abstract

A quantitative study has been made of the flow with shock waves generated in air by a sliding surface discharge lasting less than one microsecond. The high-speed flow was visualized using the shadowgraph method, the process was recorded at a rate of 124 000 frames/s, the exposure time was 1 μs. The aim of this work is to study the dynamics of the two discontinuities: the cylindrical shock wave and the contact surface generated by the discharge. Each experiment allowed several hundred images to be taken of a short-lived gas-dynamic process lasting up to 1 ms. A YOLOv8 convolutional neural network was trained and used to determine the positions of the discontinuities. A data set of 984 markups was labeled. The model on the mAP50 metric achieved 0.887 and the mAP50-95 was 0.557. The model was used to automatically measure the vertical dimensions of the contact discontinuity. It expands at times up to 0.4 - 0.8 ms to a vertical size of 5 - 11 mm. The x-t plots and the velocities of the cylindrical shock waves were measured. It is shown that up to 1 ms after the discharge, the flow development is due to the blast wind motion behind the shock wave. It is shown that the use of computer vision can significantly speed up the analysis of high-speed flow visualizations and the extraction of quantitative information.