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首页> 外文期刊>Journal of Sound and Vibration >Sound quality estimation for nonstationary vehicle noises based on discrete wavelet transform
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Sound quality estimation for nonstationary vehicle noises based on discrete wavelet transform

机译:基于离散小波变换的非平稳车辆噪声音质估计

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摘要

A new method based on the discrete wavelet transform (DWT) for sound quality estimation (SQE) of nonstationary vehicle noises is presented in this paper. Sample interior and exterior vehicle noises are first measured and denoised using the wavelet threshold method to initially lower the noise level with negligible signal distortion. A multirate filter bank combined by a set of low-pass and band-pass filters and a DWT-based filter bank are then developed for sound octave-band analysis (OBA). To build the DWT octave-band filters, the Mallat pyramidal algorithm is introduced, and five types of wavelet function with different filter lengths are investigated and compared. Finally, the Daubechies wavelet with a filter order of 35 is determined and applied to estimate sound pressure levels (SPLs) of both the interior and exterior vehicle noises. Verification results show that the newly proposed multirate-filter-based method (MF-OBA) and DWT-based method (DWT-OBA) are accurate and effective for SQE of nonstationary vehicle noises. Due to outstanding time-frequency characteristics of the wavelet analysis, the DWT-OBA can be suggested to deal with not only SQE of nonstationary vehicle noises, but also any other sound-related signal processing in engineering.
机译:提出了一种基于离散小波变换(DWT)的非平稳车辆噪声声品质估计(SQE)的新方法。首先使用小波阈值方法对样品的内部和外部车辆噪声进行测量和去噪,以在最初的噪声水平可忽略不计的信号失真下进行降低。然后,开发出由一组低通和带通滤波器组合而成的多速率滤波器组,以及基于DWT的滤波器组,用于声音倍频带分析(OBA)。为了建立DWT倍频程滤波器,引入了Mallat金字塔算法,研究并比较了五种不同滤波器长度的小波函数。最后,确定滤波器阶数为35的Daubechies小波,并将其应用于估算车辆内部和外部噪声的声压级(SPL)。验证结果表明,新提出的基于多速率滤波器的方法(MF-OBA)和基于DWT的方法(DWT-OBA)对于非平稳车辆噪声的SQE是准确有效的。由于小波分析具有出色的时频特性,因此建议将DWT-OBA不仅用于处理非平稳车辆噪声的SQE,而且还可以处理工程中任何其他与声音有关的信号处理。

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