Determining of gas type in counter flow vortex tube using pairwise fisher score attribute reduction method

This paper focused on the determining of gas types in counter flow type vortex tubes. In the present study, four different gas types including air, oxygen, nitrogen, and argon in the vortex tube with different inlet pressures and nozzle numbers have been used. The main aims of this paper are to investigate the correlations between gas types and input parameters comprising nozzle numbers, inlet pressures, inlet mass flow rate, temperature of cold outlet, temperature of hot outlet, and cold mass fraction and to select the most important attributes using correlation based attribute reduction and pairwise fisher score attribute reduction (PFSAR). After attribute reduction methods applied to dataset, k-nearest neighbor and C4.5 decision tree classifiers have been used to determine the gas type in the RHVT. The results have demonstrated that the PFSAR is a robust and efficient method in the reduction of attributes belonging to vortex tube.

► In this paper, pairwise PFSAR has been proposed and applied to investigate the correlations between gas types and input parameters belonging to RHVT. ► As feature selection process, correlation based attribute reduction has been used and compared with PFSAR. ► K-nearest neighbor and C4.5 decision tree classifiers have been used to determine the gas type in the RHVT. ► Consequently, the most significant parameters (attributes) effecting the gas types in vortex tube have been determined.