基于代理模型的麦克风相位阵列设计技术研究
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摘要
气动声学风洞试验过程中,针对目标声源特性进行麦克风相位阵列改进时,为保证风洞试验效率,必须在较短的时间内完成阵列优化设计工作。为满足这一试验需求,最大限度提升麦克风相位阵列设计效率,引入了基于Kriging代理模型的优化设计方法。采用基于点扩散函数的计算程序进行阵列性能分析,获取阵列最大旁瓣水平和分辨率。通过对样本点响应值进行计算,建立Kriging代理模型,进而以计算速度极高的Kriging代理模型作为阵列性能分析方法开展优化搜索,避免了大量调用阵列性能计算程序导致计算耗时过高的问题,显著提升了麦克风相位阵列设计效率。该阵列设计方法能够有效改善麦克风阵列的测量性能,满足声学风洞试验的特殊应用需求。
In aero-acoustic wind tunnel tests,the improvement of the microphone phase array according to the noise source features must be conducted as fast as possible to ensure the required efficiency of the tests.An optimization method based on the Kriging surrogate model is proposed in this study.The maximum sidelobe level and the resolution of the microphone phase array are obtained by analyzing the results computed from the point spread function.A Kringing surrogate model is constructed based on the response values computed on sample points.Then the surrogate model was utilized to fast assess the maximum sidelobe level and the resolution of the microphone phase array,which avoided the high computational cost caused by computing the point spread function.This method can improve the performance of the microphone phase array effectively for aero-acoustic wind tunnel tests.
In aero-acoustic wind tunnel tests,the improvement of the microphone phase array according to the noise source features must be conducted as fast as possible to ensure the required efficiency of the tests.An optimization method based on the Kriging surrogate model is proposed in this study.The maximum sidelobe level and the resolution of the microphone phase array are obtained by analyzing the results computed from the point spread function.A Kringing surrogate model is constructed based on the response values computed on sample points.Then the surrogate model was utilized to fast assess the maximum sidelobe level and the resolution of the microphone phase array,which avoided the high computational cost caused by computing the point spread function.This method can improve the performance of the microphone phase array effectively for aero-acoustic wind tunnel tests.
引文
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[22]Thomas J M.Aeroacoustic measurements[M].Berlin:Springer,2002.
[2] Ahmad D V,Radhakrishnan S.Review of acoustic measurement techniques in wind tunnels[R].AIAA-2000-2204,2000.
[3] Wei Q K.Compressive sensing based beamforming and its application in aeroacoustic experiment[R].AIAA-2014-2918,2014.
[4]周家检,郝璇,张卫民,等.相阵列技术在民机机体气动噪声研究中的应用[J].空气动力学学报,2016,34(1):91-97.Zhou J J,Hao X,Zhang W M,et al.Application of phased array technique in the research of civil airplane airframe noise[J].Acta Aerodynamic Sinica,2016,34(1):91-97.
[5]陈正武,王勋年,李征初,等.基于声学风洞的麦克风阵列测试技术应用研究[J].实验流体力学,2012,26(3):84-90.Chen Z W,Wang X N,Li Z C,et al.Application investigation of microphone array measuring and testing technique in anechoic wind tunnel[J].Journal of Experiments in Fluid Mechanics,2012,26(3):84-90.
[6] Gade S,Hald J.Array designs optimized for both low-frequency NAH and high-frequency Beamforming[R].SAE Technical Paper2005-01-4014,2015.
[7] Underbrink J R.Practical considerations in focused array design for passive broadband source mapping applications[D].Pennsylvania:Pennsylvania State University,1995.
[8]黄奔.气动噪声源的麦克风阵列识别定位技术研究[D].绵阳:中国空气动力研究与发展中心,2014.Huang B.Investigation of aerodynamic noise sources identification technique based on microphone arrays[D].Mianyang:China Aerodynamics Research and Development Center,2014.
[9] William M,Humphreys J R.Design and use of microphone direction arrays for aeroacoustic measurement[R].AIAA-98-0471,1998.
[10]Thomas F B,William M,Humphreys J R.Effect of directional array size on the measurement of airframe noise components[R].AIAA-99-1958,1999.
[11]Takeshi Ito.Aeroacoustic noise measurements in aerodynamic low-speed wind tunnels[C]//Proc of the 26th International Congress of the Aeronautical Sciences.2008.
[12]Sijtsma P.Phased array beamforming in wind tunnels[R].NLR-TP-2006-732,2006.
[13]陈宝,李周复,谭啸,等.声衬试验段环境下航空声学定位试验技术研究[J].实验流体力学,2015,22(5):78-83.Chen B,Li Z F,Tan X,et al.Investigation of aeroacoustic localization technique in lining test section[J].Journal of Experiments in Fluid Mechanics,2015,29(5):78-83.
[14]郭旺柳,宋文萍,许建华,等.旋翼桨尖气动/降噪综合优化设计研究[J].西北工业大学报,2012,30(1):73-79.Guo W L,Song W P,Xu J H,et al.An effective aerodynamics/acoustic optimization of blade tip planform for helicopter rotors[J].Journal of Northwestern Polytechnical University,2012,30(1):73-79.
[15]聂雪媛,刘中玉,杨国伟.基于Kriging代理模型的飞行器结构刚度气动优化设计[J].气体物理,2017,2(2):8-16.Nie X Y,Liu Z Y,Yang G W.Aircraft structure stiffness and aerodynamics optimization design based on Kriging surrogate model[J].Physics of Gases,2017,2(2):8-16.
[16]Kanazaki M,Tanaka K,Jeong S,et al.Multi-objective aerodynamic optimization of elements’setting for high-lift airfoil using Kriging model[R].AIAA-2006-1471,2006.
[17]Han Z H.Improving adjoint-based aerodynamic optimization via gradient-enhanced Kriging[R].AIAA-2012-0670,2012.
[18]刘俊.基于代理模型的高效气动优化设计方法及应用[D].西安:西北工业大学,2015.Liu J.Efficient surrogate-based optimization method and its application in aerodynamic design[D].Xi’an:Northwestern Polytechnical University,2015.
[19]韩忠华.Kriging模型及代理优化算法研究进展[J].航空学报,2016,37(11):3197-3225.Han Z H.Kriging surrogate model and its application to design optimization:a review of recent progress[J].Acta Aeronautica et Astronautica Sinica,2016,37(11):3197-3225.
[20]夏露,王丹.基于Kriging自适应代理模型的气动优化方法[J].航空计算技术,2013,43(1):13-17.Xia L,Wang D.Aerodynamic optimization method based on Kriging adaptive surrogate model[J].Aeronautical Computing Technique,2013,43(1):13-17.
[21]Zhang Y,Han Z H,Shi L X,et al.Multi-round surrogatebased optimization for benchmark aerodynamic design problems[R].AIAA-2016-1545,2016.
[22]Thomas J M.Aeroacoustic measurements[M].Berlin:Springer,2002.