吉林大学学报(工学版) ›› 2011, Vol. 41 ›› Issue (增刊2): 82-86.

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Sound quality prediction of vehicle interior noise based on GRNN

SU Li-li1, WANG Deng-feng1, WANG Qian2   

  1. 1. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China;
    2. College of Automotive Engineering, Jilin University, Changchun 130022, China
  • Received:2011-03-12 Online:2011-09-30 Published:2011-09-30

Abstract:

Taking 32 interior noise samples acquired from 8 types of car under different conditions as evaluation objects,loudness,sharpness,roughness and fluctuation strength,these sound metrics in psychoacoustics,were used as the input,and sensory comfortable evaluation obtained by 7 points of category scaling method as the output.The sound quality prediction model of vehicle interior noise was established based on generalized regression neutral network.Sensory comfortable of interior noise samples were obtained through the prediction model and the results were compared with obtained through back-propagation neural network and multiple linear regression prediction model.The results showed the generalized regression neutral network was more effective than back-propagation neural network and multiple linear regression prediction model,the range of relative prediction error is -7%~7%.The generalized regression neural network prediction model represented better performance on nonlinear relation between sensory comfortable and objective parameters exactly than multiple linear regression prediction model,and higher precise and stability than back-propagation neural network.

Key words: vehicle engineering, interior noise, sound quality, neural network, prediction model

CLC Number: 

  • U467.4


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