Improvement of signal-to-noise ratio of schlieren visualization images in low-density wind tunnel tests using mode-selection based signal processing
Tsuyoshi Shigeta, Takayuki Nagata, Taku Nonomura, Keisuke Asai · AIAA AVIATION 2022 Forum · 2022
View Video Presentation: https://doi.org/10.2514/6.2022-4166.vid The objective of this study is to develop digital signal processing methods that reduce noise caused by atmospheric fluctuation and image sensors and extract signal of fluid phenomena from data obtained by the highly sensitive schlieren measurement in the low-density wind tunnel. Time-series schlieren images of the flow around a triangular airfoil were used for analysis, and the effectiveness of noise reduction methods based on the randomized singular value decomposition (RSVD). In the proposed method, noise and signal of fluid phenomena were separated by frequency components using fast Fourier transform (FFT) and inverse FFT in advance, and the flow was visualized at Re = 3000 and M = 0.15, where the signal-to-noise ratio was particularly low.