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

Journal Article
2013-01-1704
ISSN: 1946-3995, e-ISSN: 1946-4002
DOI: https://doi.org/10.4271/2013-01-1704
Published April 08, 2013 by SAE International in United States
Objective Evaluation of Interior Sound Quality in Passenger Cars Using Artificial Neural Networks
Sector:
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.
Language: English

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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