Objective Evaluation of Interior Sound Quality in Passenger Cars Using Artificial Neural Networks

Paper #:
  • 2013-01-1704

Published:
  • 2013-04-08
DOI:
  • 10.4271/2013-01-1704
Citation:
Chen, S., Wang, D., Wu, Y., Liu, Z. et al., "Objective Evaluation of Interior Sound Quality in Passenger Cars Using Artificial Neural Networks," SAE Int. J. Passeng. Cars - Mech. Syst. 6(2):1078-1086, 2013, https://doi.org/10.4271/2013-01-1704.
Pages:
9
Abstract:
In this research, the interior noise of a passenger car was measured, and the sound quality metrics including sound pressure level, loudness, sharpness, and roughness were calculated. An artificial neural network was designed to successfully apply on automotive interior noise as well as numerous different fields of technology which aim to overcome difficulties of experimentations and save cost, time and workforce. Sound pressure level, loudness, sharpness, and roughness were estimated by using the artificial neural network designed by using the experiment values. The predicted values and experiment results are compared. The comparison results show that the realized artificial intelligence model is an appropriate model to estimate the sound quality of the automotive interior noise. The reliability value is calculated as 0.9995 by using statistical analysis.
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