摘要
吸尘盘作为洗扫车的关键组成部件,降低吸尘盘的气动噪声可极大提升产品性能.基于FLUENT软件和FW-H声比拟模型,对吸尘盘的气动噪声强度进行了计算,设计了一种带有肩部结构和倾斜壁面的新型吸尘盘结构,重点研究了肩部夹角和上壁面倾角对吸尘盘气动噪声产生的综合影响,基于MATLAB软件,采用多项式拟合方法分别建立了两参数与吸尘盘全压以及总声压级之间的函数关系,并结合多目标优化遗传算法对目标函数进行了优化分析.数值结果表明:肩部夹角对气动噪声的影响较为显著,在0°~20°范围内,夹角每增加1°,噪声可以降低0.4dB;合理地增大肩部夹角,可以在降低能量损失的同时有效降低吸尘盘的气动噪声,最大降幅为6.2dB.
Dust collector is the key component of the cleaning sweeper vehicle,so the product performance can be greatly improved by reducing the aerodynamic noise of the dust collector.Based on Fluent software and FW-H acoustic analogy model,the aerodynamic noise of dust collector was calculated.Firstly,a new kind of dust collector with shoul⁃der structure and inclined wall was designed in this paper,and the comprehensive influence between shoulder angle and inclined angle of upper wall on the aerodynamic noise of the dust collector was mainly focused on.Based on MATLAB software,polynomial fitting was used to establish the function relations between dust collector’s total pressure and two parameters,and between total sound pressure level and two parameters,and then the objective functions were optimized by using multi-objective optimization genetic algorithm.The numerical results show that:the shoulder angle has a signifi⁃cant influence on aerodynamic noise,and between 0°and 20°,the noise can be reduced by 0.4dB for every one degree increase of the shoulder angle.Moreover,the aerodynamic noise of the dust collector can be reduced effectively by in⁃creasing the shoulder angle reasonably while reducing the energy loss of the dust collector,and the maximum reduction is 6.2dB.
作者
单宝来
张琪昌
张沛
刘君
Shan Baolai;Zhang Qichang;Zhang Pei;Liu Jun(School of Mechanical Engineering,Tianjin University,Tianjin 300072,China;Tianjin Key Laboratory of Nonlinear Dynamics and Control,Tianjin 300072,China;Zhengzhou Yutong Heavy Industries Co.Ltd,Zhengzhou 450000,China)
出处
《动力学与控制学报》
2020年第6期90-96,共7页
Journal of Dynamics and Control
基金
国家重点研发计划(2018YFB0106200)。
关键词
吸尘盘
气动噪声
FW-H声比拟模型
多目标优化
遗传算法
dust collector
aerodynamic noise
FW-H acoustic analogy model
multi-objective optimization
genetic algorithm