| With the continuous popularization of the concept of smart kitchens,the range hood is an indispensable home appliance in the kitchen,and the performance requirements of national standards and market requirements are also constantly improved.To ensure that the range hood produces a lower noise while maintaining a high flow coefficient,the multi-wing centrifugal fan in the range hood needs to be optimized.At present,there are relatively few studies on multi-objective optimization of multi-wing centrifugal fans,and the content of related literature is also limited to the structural modification of individual components of centrifugal fans.Considering the narrow structural characteristics of the multi-wing centrifugal fan flow channel and the dynamic and static coupling effect between the volute impellers,this paper takes a multi-wing centrifugal fan for a range hood as the research object,and analyzes the structural parameters of the centrifugal fan impeller and volute Impact on performance and identify optimization variables.Based on the centrifugal fan's full pressure and noise values as optimization targets,a Co-Kriging model of related optimization variables is established,and the NSGA-II algorithm is used to conduct multi-objective optimization research on the centrifugal fan.The main research contents and research results are as follows:?1?Analyze the effect of gas viscosity on gas flow,based on the traditional volute design,optimize the profile and build a centrifugal fan model.Based on the improved RNG k-?model and LES+FW-H acoustic model,the aerodynamic performance simulation and noise simulation of the centrifugal fan were performed,and the accuracy of the calculation model was verified by corresponding experimental methods.Considering the dynamic and static coupling between the centrifugal fan volute and the impeller structure,the corresponding optimization parameters were determined by combining the corresponding flow field analysis and the derivation of some empirical formulas.Specific optimization variables include:In the impeller,the blade inlet installation angle?1A,the blade outlet installation angle?2A,and the blade width B are selected as optimization variables;In the volute,the volute radius R and the volute opening degree A1 were selected as optimization variables.At the same time of determining the optimization variables,by analyzing the impact of the above structural parameter changes on the aerodynamic performance of the fan,the parameter ranges of each optimization variable were determined;?2?Considering the large number of optimization variables,the Co-Kriging model with high reliability is used to predict the performance of the wind turbine.The relationship between high-confidence samples and low-confidence samples and the accuracy of the Co-Kriging model was analyzed by establishing a bivariate multi-peak function.It was found that when the number of low-confidence sample points reached about 8 times that of high-confidence sample points.Co-Kriging model can maintain sufficient prediction accuracy.Therefore,in the sample design process,the optimal Latin hypercube design method was used to select 100 parameter combinations.Among them,90 sets of data are obtained through numerical simulation and corresponding target results are used as low-confidence sample sets,and the remaining 10 sets of data are obtained through experiments as target results and used as high-confidence sample sets.The remaining 85 groups of data were randomly selected to construct the Co-Kriging model,and the remaining 15 groups of data were used to verify the accuracy of the Co-Kriging model;?3?The performance prediction of multi-wing centrifugal fans based on the Co-Kriging model shows that the maximum relative error of full-pressure prediction of multi-wing centrifugal fans is 3.47%;The maximum relative error of noise prediction is 2.13%,ensuring that the agent model is feasible in the field of centrifugal fan performance optimization.Then,the aerodynamic performance parameters and noise parameters of the wind turbine are used as optimization targets,and the NSGA-?algorithm is used to perform optimization analysis to obtain the Pareto optimal solution set.Considering that the full pressure and noise performance of a multi-wing centrifugal fan cannot be optimized at the same time,the noise value is kept low under the condition that the full pressure meets the design requirements.Finally,a group of multi-wing centrifugal fan structures are selected in the Pareto solution.Parameters as the optimization result.After optimization,the full pressure of the fan is increased by 30 Pa compared to the prototype,and the average sound pressure level of the fan is reduced by 3.2 d B;?4?Combine the optimization results to make a prototype,and perform the corresponding aerodynamic performance test and noise test.Because the existing noise test system cannot accurately simulate the test state of the maximum air volume point in the aerodynamic performance test during the test,the experimental device for noise test was improved to obtain more accurate noise results.Based on the results of aerodynamic experiments and noise experiments,the performance of the optimized centrifugal fan is analyzed.The results show that:After optimization,the internal flow field of the multi-wing centrifugal fan is improved,the aerodynamic performance is effectively improved,and the range of stable conditions is expanded.In the vicinity of the design condition point,the total pressure rises by about 27 Pa,and the average noise decreases by about 3.0 d B.Aiming at the limitations of the current multi-wing centrifugal fan optimization research process,this paper proposes a novel optimization scheme:Considering the dynamic and static coupling between the impeller and the volute,the corresponding optimization variables were selected,and the high-reliability Co-Kriging model was used to predict the aerodynamic performance of the multi-wing centrifugal fan.Combined with NSGA-?optimization algorithm for optimization design,a set of Pareto optimal solution set was finally obtained,which provided a scientific basis for the application of approximate models in impeller machinery. |
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