An extension of digital PIV-processing to double-exposed images

Abstract

 In this paper digital processing techniques for PIV (Partical Image Velocimetry) using double-exposed particle images have been studied. It has been found that a pattern matching technique is significantly superior to the traditional autocorrelation method in the case that a large particle displacement between the double exposures is present on the image. In PIV using double-exposed images, the image shifting technique is usually used to solve the directional ambiguity problem. The performance of PIV using autocorrelation technique is dependent on the flow speed and the amount of image shift applied. This dependence, for example, causes a difficulty of autocorrelation in flows close to a solid boundary. The present study shows that a pattern matching technique eliminates such a difficulty. At the same signal-to-noise ratio, the pattern matching techndique has a better spatial resolution than that of autocorrelation. In concert with the pattern matching technique, PID (Particle Image Distortion) can be applied to double-exposed images, further improving the reliability and accuracy of velocity estimates of PIV in the presence of large velocity gradients. Generally speaking, PIP-matching and PID extend the validity of PIV using double-exposed images. The total processing time required by the PIV using the pattern matching technique and one PID iteration is of the same order as that required by the PIV using autocorrelation.