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Analysis on vehicle sound quality via deep belief network and optimization of exhaust system based on structure-SQE model
Applied Acoustics ( IF 3.4 ) Pub Date : 2021-01-01 , DOI: 10.1016/j.apacoust.2020.107603
Y. Qiu , E.L. Zhou , H.T. Xue , Q. Tang , G. Wang , B. Zhou

Abstract The sound quality of vehicle interior noise is under a deep influence of the exhaust noise determined by exhaust system, playing a significant role in the customer perception of passenger car. Therefore, in this paper, the relationship between the structure parameter of exhaust system and the sound quality of vehicle interior noise was indicated and a structure-SQE model was proposed. As the basis of this study, an exhaust system was prepared and six parameters of it were selected as variables. Through setting different values for these variables, eighteen simulation samples were designed by orthogonal experiment. The sound pressure levels of vehicle interior noises corresponding to these examples were obtained through the Transfer Path analysis (TPA). Afterwards, a subjective and objective evaluation model was utilized to estimate satisfaction scores of interior noises of eighteen models. With the satisfaction scores and values of structure parameters, the contributions and main effects of structure parameters on the satisfaction were analyzed and the structure-SQE model was developed via deep belief network (DBN) algorithm. In addition, an improvement for better satisfaction was conducted.

中文翻译:

基于深度置信网络的汽车声品质分析及基于结构-SQE模型的排气系统优化

摘要 车内噪声的声品质深受排气系统决定的排气噪声的影响,对乘用车的顾客感知起着重要作用。因此,本文指出了排气系统结构参数与车内噪声声品质的关系,提出了结构-SQE模型。作为这项研究的基础,准备了一个排气系统,并选择了它的六个参数作为变量。通过为这些变量设置不同的值,通过正交实验设计了十八个模拟样本。对应于这些示例的车辆内部噪声的声压级是通过传输路径分析 (TPA) 获得的。然后,采用主客观评价模型对18款车型的室内噪声满意度评分进行评估。通过结构参数的满意度得分和取值,分析了结构参数对满意度的贡献和主要影响,并通过深度置信网络(DBN)算法建立了结构-SQE模型。此外,还进行了提高满意度的改进。
更新日期:2021-01-01
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