Abstract
The paper presents the results of using the PTV method to study the motion of the liquid phase in the interblade channel of the turbine blade cascade in a wet steam flow. A method for processing vector fields of a polydisperse droplet flow is developed on the basis of machine learning algorithms (namely, the Bayesian Gaussian Mixture Data Modeling and the Kernel Density Algorithm). Using the PTV method together with these algorithms makes it possible to study complex polydisperse wet steam flows in more detail. On the basis of this, characteristic droplet streams and their trajectories are determined in the interblade channel of the turbine blade cascad.
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