Sound quality prediction and improving of vehicle interior noise based on deep convolutional neural networks

2020 ◽  
Vol 160 ◽  
pp. 113657
Author(s):  
Xiaorong Huang ◽  
Haibo Huang ◽  
Jiuhui Wu ◽  
Mingliang Yang ◽  
Weiping Ding
2016 ◽  
Vol 113 ◽  
pp. 149-161 ◽  
Author(s):  
Hai B. Huang ◽  
Xiao R. Huang ◽  
Ren X. Li ◽  
Teik C. Lim ◽  
Wei P. Ding

Author(s):  
Gangping Tan ◽  
Gang Jie ◽  
Ming Cao

An optimization strategy of sound quality was proposed to improve sound quality inside a vehicle. The frequency of vehicle interior noise was divided into sub-bands by equivalent rectangular bandwidth (ERB) in the frequency domain, and the intensity of sub-band noise located in the mid-low frequency can be modified by using the measure of active noise control (ANC) in order to analyze its influence on the sound quality of original noise. Orthogonal experiments of vehicle interior noise were conducted according to experimental design. A model of sound quality objective evaluation (SQOE) was proposed as an experimental index. The role of sub-band on the model of SQOE was analyzed at different speeds so as to achieve the optimum level, optimum combination of sound quality and main factors. The results, obtained by implementing the optimization strategy of sound quality, were verified by means of tests. By validation, it showed that optimum sound quality can be achieved by changing the intensity of sub-band noise.


Author(s):  
In Hyung Yang ◽  
O. Cheol Kwon ◽  
Jung Youn Lee ◽  
Jae-Eung Oh

The reduction of the Vehicle interior noise has been the main interest of NVH engineers. The driver’s perception on the vehicle noise is affected largely by psychoacoustic characteristic of the noise as well as the SPL. In particular, the HVAC sound among the vehicle interior noise has been reflected sensitively in the side of psychology. In previous study, we have developed to verify identification of source for the vehicle HVAC system through multiple-dimensional spectral analysis. Also we carried out objective assessments on the vehicle HVAC noises and subjective assessments have been already performed with 30 subjects. In this study, the linear regression models were obtained for the subjective evaluation and the sound quality metrics. The regression procedure also allows you to produce diagnostic statistics to evaluate the regression estimates including appropriation and accuracy. Appropriation of regression model is necessary to R2 value and F-value. And testing for regression model is necessary to Independence, Homoscedesticity and Normality. To enhance sound quality, we applied active noise control (ANC) which is effective in the low-frequency bandwidth. Primary noise of the HVAC system is less than 500Hz. As a result of ANC application, sound quality is improved by more quiet, powerful, expensive, smooth.


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