Detection of drops measured by the time shift technique for spray characterization

Characterizing drops in a spray process is of high interest in many areas, such as car painting or spray drying. The Time Shift (TS) technique provides an efficient and accurate way to optically measure size and velocity of individual droplets in sprays. Its realization in practice is not wide spread, thus the necessary signal processing of the measured data has not yet been fully developed or optimized. However, the TS technique is the only technique deemed suitable for online spray monitoring. In this study, we derive a filtering concept by using only a single filter that can be used for detection of droplets measured by the TS technique. We show that our approach is optimal in terms of detection power. Additionally, we show that the average detection power does not exceed certain limits, close to the one of a conventional matched filter bank.