Real-time adaptive particle image velocimetry for accurate unsteady flow field measurements

Almost all conventional open-loop particle image velocimetry (PIV) methods employ fixed-interval-time optical imaging technology and the time-consuming cross-correlation-based PIV measurement algorithm to calculate the velocity field. In this study, a novel real-time adaptive particle image velocity (RTA-PIV) method is proposed to accurately measure the instantaneous velocity field of an unsteady flow field. In the proposed closed-loop RTA-PIV method, a new correlation-filter-based PIV measurement algorithm is introduced to calculate the velocity field in real time. Then, a Kalman predictor model is established to predict the velocity of the next time instant and a suitable interval time can be determined. To adaptively adjust the interval time for capturing two particle images, a new high-speed frame-straddling vision system is developed for the proposed RTA-PIV method. To fully analyze the performance of the RTA-PIV method, we conducted a series of numerical experiments on ground-truth image pairs and on real-world image sequences.