上下送风型空气净化器风道迎风角优化设计
Optimization design of windward angle of air duct of upper and lower air supply purifiers
摘要：
以上下送风的立式大型空气净化器为研究对象,基于ANSYS有限元仿真分析软件建立了风道流体模型,对空气净化器风道结构进行了0°～90°多迎风角下的气流流动特性仿真分析,以模拟实际空气净化器的内部流场。采用BP神经网络表征空气净化器风道中迎风角对风道内流速、压降的非线性映射关系,在保证空气过滤净化时效性的条件下,依据神经网络模型预测结果,采用遗传算法寻优得到的最佳迎风角为15.9°,相比未进行优化的空气净化器风道结构,出、入口流速分别提高8.4%、14.5%,每小时增加洁净空气量352.21 m3。
Abstract：
Taking large-scale vertical air purifiers with upper and lower air supply as the research object, based on ANSYS finite element simulation analysis software, an air duct fluid model is established, and the air flow characteristics of the air duct structure of the air purifier under multiple windward angles of 0° to 90° are simulated and analysed to simulate the internal flow field performance of the air purifier in real. Using backpropagation neural network to characterize the nonlinear mapping relationship between the windward angle of the air purifier duct and the flow velocity and pressure drop inside the air duct. Under the condition of ensuring the timeliness of air filtration and purification, based on the prediction results of the neural network model, the optimal windward angle obtained by genetic algorithm is 15.9°, which increases the flow velocity of the outlet and inlet by 8.4% and 14.5% respectively compared with the unoptimized air duct structure, and increases the clean air volume by 352.21 m3per hour.
Keywords:air purifier; air duct optimization; finite element simulation; backpropagation neural network; genetic algorithm