基于响应面法的乘用车消声器声学性能优化

摘要/Abstract

摘要： 针对某乘用车车内、外消声器中频段(0.5~1.5kHz)降噪能力较差的问题，利用响应面法对消声器在中频段的传递损失进行优化.首先，采用Latin超立方法对插入管长度、穿孔板位置和穿孔率等设计变量进行采样，采用声学有限元法计算各样本点在中频段的传递损失；然后，利用Kriging模型建立中频段传递损失的响应面模型，并验证其计算精度；最后，利用遗传算法对该响应面模型的计算结果进行优化.结果表明，与优化前消声器在中频段的传递损失(27.05dB)相比，优化后消声器在中频段的传递损失(41.38dB)增加了14.33dB，其消声性能得到了明显改善.

关键词: , 消声器；声学性能优化；传递损失；响应面模型

Abstract: The noises in the interior and exterior of a vehicle are measured in a stationary test, and the results reveal that noise reduction capability of its exhaust muffler is quite weak in the midfrequency. In order to improve the midfrequency transmission loss (TL) of the muffler, optimization is conducted based on the response surface method (RSM). Firstly, the length of insert tubes, position of perforated plates, perforation rate, etc. are selected as design variables and are sampled by the Latin hypercube method, and the frequencyaveraged TL of each sampled point is calculated by acoustic finite element method. Secondly, an RSM model of the midfrequency TL is developed by the Kriging surrogate technique, and its accuracy is validated by reanalysis. Finally, based on this model, the midfrequency TL is optimized by genetic algorithm. After optimization the midfrequency TL is 41.38dB increasing 14.33dB than the original value 27.05dB, and also the overall noise reduction performance of this muffler is improved significantly. The RSMbased optimization procedure in this paper provides a guideline for the acoustic performance design of the mufflers.

Key words: muffler, acoustic performance optimization, transmission loss (TL), response surface method (RSM) model

中图分类号:

李明瑞1，邓国勇2，米永振1，郑辉1. 基于响应面法的乘用车消声器声学性能优化[J]. 上海交通大学学报（自然版）, 2017, 51(9): 1031-1035.

LI Mingrui1,DENG Guoyong2,MI Yongzhen1,ZHENG Hui1. Acoustic Performance Optimization of the Exhaust Muffler for a Car Based on Response Surface Method[J]. Journal of Shanghai Jiaotong University, 2017, 51(9): 1031-1035.

参考文献

［1］林森泉, 侯亮, 黄伟, 等. 基于GTpower的消声器优化设计［J］. 厦门大学学报(自然科学版), 2013, 52(3): 376381.
LIN Senquan, HOU Liang, HUANG Wei, et al. Optimization design of the muffler based on GTpower［J］. Journal of Xiamen University (Natural Science), 2013, 52(3): 376381.
［2］程春, 李舜酩, 贾骁. 传递矩阵法的排气消声器声学性能分析［J］. 噪声与振动控制, 2013(4): 126130.
CHENG Chun, LI Shunming，JIA Xiao. Acoustic performance analysis of exhaust muffler using transfer matrix method［J］. Noise and Vibration Control, 2013(4): 126130.
［3］王雪仁, 季振林. 有流消声器四极参数和传递损失的边界元法预测［J］. 计算物理, 2007, 24(6): 717724.
WANG Xueren, JI Zhenlin. Boundary element analysis of fourpole parameters and transmission loss of silencers with flow［J］. Chinese Journal of Computational Physics, 2007, 24(6): 717724.
［4］徐贝贝, 季振林. 穿孔管消声器声学特性的有限元分析［J］. 振动与冲击, 2009, 28(9): 112115.
XU Beibei, JI Zhenlin. Finite element analysis of acoustic attenuation performance of perforated tube silencers［J］. Journal of Vibration and Shock, 2009, 28(9): 112115.
［5］段翠云, 崔光, 刘培生. 多孔吸声材料的研究现状与展望［J］. 金属功能材料, 2011, 18(1): 6065.
DUAN Cuiyun, CUI Guang, LIU Peisheng. Present research and prospect of porous absorption materials［J］. Metallic Functional Materials, 2011, 18(1): 6065.
［6］SHIELDS M D, ZHANG J. The generalization of Latin hypercube sampling［J］. Reliability Engineering & System Safety, 2016, 148: 96108.
［7］OLIVER M A, WEBSTER R. Kriging: A method of interpolation for geographical information systems［J］. International Journal of Geographical Information Systems, 1990, 4(3): 313332.
［8］季振林. 消声器声学理论与设计［M］. 北京：科学出版社, 2015.
［9］CHIU M. Shape optimization of multichamber mufflers with pluginlet tube on a venting process by genetic algorithms［J］. Applied Acoustics, 2010, 71(6): 495505.

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