摘要
由于在实际应用中噪声频谱的巨大差异,且不同吸声材料在不同频段的吸声性能也不尽相同,为提高噪声控制的效率和应用可行性,根据实际降噪的需求,选择多种群遗传算法对常用的复合吸声结构的各项参数进行按需优化设计,使得设计的复合吸声结构可以适用于不同应用场合。实验结果表明:与标准遗传算法的结果相比,多种群遗传算法的优化结果显著改善了复合吸声结构的吸声性能以及吸声带宽。微穿孔板复合结构可以适用于低频噪音环境,而多孔材料和微穿孔板的复合结构在中高频噪音环境中具有优异的吸声性能,现实生活中可根据适用环境选择对应的具有优异性能的吸声结构。
Due to the huge difference in noise spectrum in different practical applications,the sound-absorption performance of different sound absorbing materials in different frequency bands is not identical.In order to improve the efficiency and feasibility of noise control,according to the actual noise reduction requirements,multi-population genetic algorithm is selected to optimize the parameters of the commonly used composite sound-absorbing structure on demand,so that the designed composite sound-absorbing structure can be suitable for different applications.The experimental results show that compared with the standard genetic algorithm,the optimization results of multi-population genetic algorithm significantly improve the sound absorption performance and sound absorption bandwidth of the composite structure.The composite structure of micro-perforated plate can be suitable for low frequency noise environment,while the composite structure of porous material and micro-perforated plate has excellent sound absorption performance in medium and high frequency noise environment.In real life,the corresponding sound absorption structure with excellent performance can be selected according to the applicable environment.
作者
王永华
薄志伟
刘哲明
于化东
WANG Yong-hua;BO Zhi-wei;LIU Zhe-ming;YU Hua-dong(Changchun University of Science and Technology,Ministry of Education Key Laboratory for Cross-Scale Micro and Nano Manufacturing,Jilin Changchun 130022,China;Jilin University,Key Laboratory of Bionic Engineering,Ministry of Education,Jilin Changchun 130022,China)
出处
《机械设计与制造》
北大核心
2023年第6期73-78,共6页
Machinery Design & Manufacture
基金
国家自然科学基金(51705033)
吉林省教育厅(JJKH20190560KJ)
吉林省科技厅(20190103001JH)。
关键词
微穿孔板
多孔材料
复合吸声结构
多种群遗传算法
优化设计
Micro-Perforated Plate
Porous Material
Composite Sound-Absorbing Structure
Multi-Population Genetic Algorithm
Optimal Design
