An adaptive algorithm for cross-correlation velocity measurement

In this paper, a novel method for particle velocity measurement by using the cross-correlation algorithm is proposed. The predicted transit time is used to implement an adaptive process for selecting signal segments that are of higher overlap degree. The proposed algorithm improves the cross-correlation coefficient and provides a way to detect the transit time with a higher accuracy. Simulations are carried out to evaluate the proposed adaptive algorithm by comparing it with the conventional algorithm. The comparison results demonstrate that the cross-correlation coefficient obtained by the adaptive algorithm is larger than that obtained by the conventional algorithm, and hence the transit time is more accurate.