No abstract

Considering that there are many design variables in multi-blade centrifugal fans, the complicated design parameters and internal flow uncertainty increase the difficulty of studying fan noise mechanisms. This study adopted the impact noise between the airflow at the impeller outlet inside the fan and the volute tongue as the research object. Based on the influence of mutual interfering noise sources on the system noise, a partial coherence function was introduced to establish a system noise model. The correlation between the static pressure of the impeller outlet in the volute tongue area of the centrifugal fan and far-field noise of the fan was analyzed and obtained. The peak values of fundamental frequency and average sound pressure level of a far-field noise receiving points were selected as the optimization goals, taking the volute tongue placement angle θ1, volute tongue radius R, and center distance L1 as the optimization objects. The Latin hypercube sampling was used to select 35 groups of sampling points and a Kriging agent model was established. The NSGA-II genetic algorithm was used to optimize the volute tongue profile. The results showed that the flow rate was increased by 1.2 m3/min, the far field noise of the centrifugal fan was reduced by 1.9 dB, while the fan efficiency increased by 3%, static pressure increased by 27 Pa, and peak values of fundamental frequency reduced by 8%.

The traditional single-arc blade used in the squirrel cage fan is simple in structure and cannot meet relevant parameterized design requirements. In order to improve the aerodynamic performance of single-arc blades of squirrel cage fans an improved Hicks-Henne function was used in this study to parameterize the blade expression in a Q35 single-suction squirrel cage fan. The AE criterion was used to optimize the Latin hypercube design, a Co-Kriging agent model was established with High and low confidence samples, and the NSGA-II algorithm was combined with the flow rate and total pressure efficiency as a multi-objective optimization goal. A set of optimal blade parameters was selected under the premise that the flow meets the design requirements. The optimized fan's total pressure and total pressure efficiency were improved at each working point. At the design working point, the fan's total pressure increased by about 23Pa, the effective air volume increased by 1.18m³/min, and the total pressure efficiency improved by 3.31%.