Inference System Based on Fuzzy Clustering to Display the Flow Field Changes in the Rotor Outlet of Centrifugal Turbomachinery

In this paper, a fuzzy clustering system is presented to display the flow field changes in the rotor outlet of centrifugal . What is important in the research done in the field of is the need for all the fields to properly understand the phenomena of flow inside the , which has complexities. For this reason, the most advanced laboratory equipment is used in this regard, which is associated with issues such as time consuming, high costs, and a large number of required tests, and doubles the importance of simulating and observing current phenomena through artificial intelligence algorithms. The present system operates on the basis of fuzzy clustering so that the spatial data (from the PIV measurement system) by the number of specific clusters to the field display in the initial time; then, by applying changes to the cluster related to the time series (from the system measurement of LDA) that contains the recorded changes of the current during the time of the data mining, the new field data are obtained at a new time step and the clustering of the data shows the variation of the flow field in the fuzzy environment. In this paper, the flow field was investigated for 6 successive steps, and the results of the system output showed the variation of the flow field from the rotor at different angles.