Abstract
The evaluation of the sound quality of door-slamming has become one of the important issues in vehicle noise, vibration and harshness (NVH) analysis. For the sound quality evaluation of door-slamming, a new sound metric, named as sound metric based on critical band wavelet decomposition (SMCBWD), is developed. In the new sound metric, the sound signals of door-slamming are sampled and the signal component of the door-slamming sound which has the great influence on the quality of door-slamming is extracted by using the leaky integration method. The extracted signal component is then decomposed by wavelets based on the critical bands and the coefficients of wavelet decomposition are calculated. Based on the energy of the frequency weighted wavelet decomposition coefficients, the new sound metric, SMCBWD, is calculated. In order to verify the effectiveness of SMCBWD, the correlation coefficients between the new sound metric and the subjective sound quality performance value of door-slamming, as well as between the traditional sound metrics (loudness, sharpness) and the subjective sound quality performance value of door-slamming have been calculated, respectively. The results show that the new sound metric developed in this paper has the higher correlations with the subjective sound quality performance value when compared with the traditional sound metric of loudness and sharpness. Thus, SMCBWD can be used to evaluate the sound quality of door-slamming more accurately.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Chandrika, U. K. and Kim, J. H. (2010). Development of an algorithm for automatic detection and rating of squeak and rattle events. J. Sound and Vibration 329, 21, 4567–4577.
Ishibashi, M., Preis, A. and Satoh, F. (2006). Relationships between arithmetic averages of sound pressure level calculated in octave bands and Zwicker’s loudness level. Applied Acoustics 67, 7, 720–730.
Lee, H. and Kwon, O. (2007). Modeling of door slam noise index by using sound quality metric. SAE Paper No. 2007-01-2394.
Lee, H. H. and Lee, S. K. (2009). Objective evaluation of interior noise booming in a passenger car based on sound metrics and artificial neural networks. Applied Ergonomics 40, 5, 860–869.
Lee, S. K. (2008). Objective evaluation for the passenger car during acceleration. J. Sound and Vibration 310, 1–2, 149–168.
Lee, S. K., Kim, H. W. and Na, E. W. (2010). Improvement of impact noise in a passenger car utilizing sound metric based on wavelet transform. J. Sound and Vibration 329, 17, 3606–3619.
Mao, D., Gao, Y. and Yu, W. (2005). Grouped pair-wise comparison for subjective sound quality evaluation. Acta Acustica 30, 6, 515–520.
Shen, X., Zuo, S. and Li, L. (2009). BP neural network prediction of car interior sound quality. Technical Acoustics 28, 3, 264–268.
Shen, X., Zuo, S. and Li, L. (2010). Interior sound quality forecast for vehicles based on support vector machine. J. Vibration and Shock 29, 6, 66–68.
Wang, Y. S., Lee, C. M. and Kim, D. G. (2007). Sound quality prediction for nonstationary vehicle interior noise based on wavelet pre-processing neural network model. J. Sound and Vibration 299, 4–5, 933–947.
Zhu, X. and Kim, J. (2010). Application of analytic wavelet transform to analysis of highly impulsive noises. J. Sound and Vibration 294, 4–5, 841–855.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Yang, C., Yu, D. & Xia, B. Research on the sound metric of door-slamming sound based on leaky integration and wavelet decomposition. Int.J Automot. Technol. 15, 853–860 (2014). https://doi.org/10.1007/s12239-014-0089-4
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12239-014-0089-4