Speed Detection in Wind-tunnels by Processing Schlieren Images

Schlieren imaging in wind-tunnels is extensively utilized to study the effects of air on an airplane surface. One of the interesting subjects for research is to study the effects of speed change on the airplane surface. Speed change results in occurrence of shock waves, which are visualized as lines on Schlieren images. In this paper, we study the problem of detecting speed of a plane after occurrence of a shock wave. For this, a two-level scheme is utilized which involves Schlieren image processing and classification. In the first stage, favorite features are extracted from a Schlieren image, which are represented as a feature vector. In the second stage, a classification system is proposed which categorizes Schlieren images according to their features. Each class represents one specific case of speed change. Experimental results are conducted in Wind-Tunnel laboratory of the Malek Ashater University of Technology and show a perfect accuracy rate.