Abstract

This paper presents an experimental study of the optimization of blade skew in low pressure axial fan. Using back propagation (BP) neural network and genetic algorithm (GA), the optimization was performed for a radial blade. An optimized blade is obtained through blade forward skew. Measurement of the two blades was carried out in aerodynamic and aeroacoustic performance. Compared to the radial blade, the optimized blade demonstrated improvements in efficiency, total pressure ratio, stable operating range, and aerodynamic noise. Detailed flow measurement was performed in outlet flow field for investigating the responsible flow mechanisms. The optimized blade can cause a spanwise redistribution of flow toward the blade midspan and reduce tip loading. This results in reduced significantly total pressure loss near hub and shroud endwall region, despite the slight increase of total pressure loss at midspan. In addition, the measured spectrums show that the broadband noise of the impeller is dominant.