OPTIMIZATION OF LOW NOISE BIONIC FAN USING GRAY RELATIONAL ANALYSIS COUPLED WITH ENTROPY MEASUREMENT

Abstract

This research presents a hybrid optimization method for the determination of the optimal geometry parameters which can minimize the A-weighted sound pressure level of bionic fan on condition that the mass flow rate of the bionic fan is as high as possible. A hybrid approach of gray relational analysis (GRA), Taguchi method, and entropy measurement has been used to obtain better acoustic performances with three basic geometry parameters, which are blade number, boss ratio, and blade stagger angle. A L9(34) orthogonal array has been used for conducting the experiment for optimization of flow and acoustic performances. The problem of multiple performance indices is simplified into single performance index by using gray relational grade. The designed experimental results are utilized in GRA, and the weights of the flow and acoustic performances are determined by using the entropy measurement method. Meanwhile, the optimal combination of bionic fan parameters is determined by using GRA method. Moreover, the validation tests show that the overall sound pressure level (SPL) reduces by 15.50% at the cost of mass flow rate reducing by 3.00%. The comparison of the A-weighted SPL for acoustic tests between original fan and optimized bionic fan demonstrates that the acoustic performance obviously improve from 20 Hz to 6300 Hz. Therefore, it is clearly shown that the proposed approach in this paper can be an useful tool to improve acoustic performance of bionic fan.