噪声与振动控制2025，Vol.45Issue(3)：68-73,174,7.DOI:10.3969/j.issn.1006-1355.2025.03.011
超薄宽频复合层合板结构吸声机理及其优化设计
Sound Absorption Mechanism and Its Optimal Design of an Ultra-thin Broadband Composite Laminate Structure
摘要
Abstract
The traditional lightweight composite sound-absorbing structure has insufficient sound absorption perfor-mance in medium-frequency broadband,which limits its practical application in some transport means,such as automobiles,high-speed trains and aircraft.Based on the principle of composite sound absorption,this paper designed and optimized an ultra-thin broadband composite laminate sound-absorbing structure,which improves the performance of medium-frequency and large-bandwidth sound absorption under the condition of small size,in order to realize the lightweight design of the sound-absorbing structures.Firstly,an ultra-thin broadband composite laminate sound-absorbing structure was designed,and the correctness of the model was verified through simulation.Secondly,to address the problem of numerous parameters af-fecting the acoustic performance of composite plywood structures,a main effect analysis model was established to realize the dimension reduction of structural design parameters.Finally,aiming at the multi-parameter nonlinear optimization prob-lem of sound-absorbing structure performance,an optimization model combining radial basis function(RBF)neural network and adaptive simulated annealing(ASA)was established.The optimization results show that compared with traditional sound-absorbing structures,the composite laminate sound-absorbing structure has better sound-absorbing performance under the same size conditions,and the structural thickness is only 1/15 of the center frequency wavelength,which means to have good lightweight effect.关键词
声学/吸声结构/优化设计/Pareto图/RBF神经网络/自适应模拟退火Key words
acoustics/sound absorption structures/optimal design/Pareto diagram/RBF neural networks/adaptive simulated annealing分类
通用工业技术引用本文复制引用
罗哲,谭刚,杨钰,王林惠,王鑫昱..超薄宽频复合层合板结构吸声机理及其优化设计[J].噪声与振动控制,2025,45(3):68-73,174,7.基金项目
湖南省教育厅科学研究资助项目(23B0757) （23B0757）
湖南省自然科学基金资助项目(2023JJ50071) （2023JJ50071）
湖南省社会科学成果评审委员会课题资助项目(XSP2023JJC024) （XSP2023JJC024）
