首页> 外文期刊>International Journal of Automotive Technology >MULTI-OBJECTIVE OPTIMIZATION OF SOUND PACKAGE PARAMETERS FOR INTERIOR HIGH FREQUENCY NOISE OF HEAVY-DUTY TRUCK USING GREY THEORY
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MULTI-OBJECTIVE OPTIMIZATION OF SOUND PACKAGE PARAMETERS FOR INTERIOR HIGH FREQUENCY NOISE OF HEAVY-DUTY TRUCK USING GREY THEORY

机译:基于灰色理论的重型卡车内部高频噪声声包参数多目标优化

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摘要

This article presents a new idea by applying different sound package parameters of to improve the acoustic performance of the commercial vehicle cab. A statistical energy analysis model of the commercial vehicle cab was created, and the SPL of the interior noise for the commercial vehicle cab was predicted and validated at speed of 80 km/h. The contributions of some major subsystems to interior noise were obtained at 80 km/h. Two major characteristics of interior SPL and total weight of sound packages were determined as the optimization targets. The thicknesses of the sound packages for floor, roof, front wall and rear wall were selected to be the optimal variables. The orthogonal array table with four factors and three levels are selected for the experimental design. The optimal combination of sound package parameters is determined by using grey relational analysis with Taguchi method. A grey relational grade is acquired from the analysis to optimize multiple performance characteristics. The experimental results show that the presented methods can effectively deal with the information redundancy problem with multiple sound package parameters for commercial vehicle cab.
机译:本文提出了一种通过应用不同的声音包参数来改善商用车驾驶室声学性能的新思路。建立了商用车驾驶室的统计能量分析模型,并以80 km / h的速度预测和验证了商用车驾驶室的内部噪声的SPL。以80 km / h的速度获得了一些主要子系统对室内噪声的贡献。内部SPL和声音包总重量的两个主要特征被确定为优化目标。选择用于地板,屋顶,前壁和后壁的声音包的厚度作为最佳变量。选择具有四个因子和三个级别的正交阵列表进行实验设计。声音包参数的最佳组合是通过使用Taguchi方法进行灰色关联分析来确定的。从分析中获取灰色关联等级,以优化多个性能特征。实验结果表明,所提出的方法可以有效地解决商用车驾驶室具有多个声音包参数的信息冗余问题。

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