Hydrogen leakage diagnosis has attracted more and more attention, especially in the high-pressure hydrogen system of fuel cell vehicles, where the chance of deflagration is quite high. Traditional methods for detecting gas leaks rely on stationary sensor measurements and manual inspections. Manual inspections are time and resource-consuming, and it is challenging to achieve real-time, comprehensive inspections in large spaces. In this study, a new Adaptive Stream Stripe-Background Oriented Schlieren (ASS-BOS) method for hydrogen jet visualization is proposed. Three different background patterns, namely random scatter background, checkerboard background, and stripe background, are designed for multiple experiments. The results show that when observing hydrogen jets in the far-field region (low-density gradient), ASS-BOS has higher accuracy and resolution, detects larger background displacements, and shows more turbulence details. In addition, the concentration distribution of the hydrogen jet is reconstructed using ASS-BOS. We compare the concentration of the hydrogen jet obtained from the inversion of the ASS-BOS method with the experimental results measured by the sensor. We find that the average error is 3.45%, indicating that ASS-BOS can accurately reconstruct the concentration distribution of the hydrogen jet.
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