| 金可心,卢海峰,杨 亮,褚志刚.融入时频能量特征的车内噪声声品质评价方法[J].电子测量与仪器学报,2022,36(5):96-103 |
| 融入时频能量特征的车内噪声声品质评价方法 |
| Sound quality evaluation method of vehicle interior noise basedon time-frequency energy characteristics |
| |
| DOI： |
| 中文关键词: 车内噪声 声品质 变分模态分解 能量特征 GA-BP 神经网络 |
| 英文关键词:vehicle interior noise sound quality variational mode decomposition energy characteristic GA-BP neural network |
| 基金项目:国家自然科学基金（11774040）项目资助 |
|
|
|
|
| 摘要点击次数: 1236 |
| 全文下载次数: 1245 |
| 中文摘要: |
| 为提升车内噪声声品质评价的准确性,建立了一种融入时频能量特征的车内噪声声品质评价方法。 该方法首先对车内
噪声信号进行变分模态分解获得本征模态分量,再基于 Hilbert 变换得到各分量的瞬时强度及计权能量,进而获得信号的时频
能量特征;在此基础上,建立了以心理声学客观参量和时频能量特征为联合输入的遗传算法优化反向传播神经网络声品质评价
模型。 应用建立方法对某汽车车内噪声声品质进行评价,其结果与主观评价结果的相关度达 93. 7%、相对误差小于 8. 0%,该车
车内噪声声品质被准确评价。 建立的融入时频能量特征的车内噪声声品质评价方法准确性高,在汽车声品质开发实践中具有
良好应用前景。 |
| 英文摘要: |
| In order to accurately evaluate the interior noise, a sound quality evaluation method of interior noise based on time-frequency
energy characteristics is proposed. First, the noise signal is adaptively decomposed by variational modal decomposition, and a series of
intrinsic modal function components are obtained. Then, the instantaneous intensity and weighted energy of each component are obtained
through Hilbert transform, which are used as the time-frequency energy characteristics of the noise signal. On this basis, a sound quality
evaluation model based on genetic algorithm optimal back propagation (GA-BP) neural network is established with the time-frequency
energy characteristics and the psychoacoustic parameters as the input. The proposed method is used to evaluate the interior noise of a
vehicle. The correlation between the results and the subjective evaluation results reach 93. 7%, and the relative error is less than 8. 0%,
which accurately reflects the sound quality of the vehicle interior noise. The proposed method enjoys a high accuracy and has a good
application prospect in the practice of vehicle sound quality development. |
| 查看全文 查看/发表评论 下载PDF阅读器 |
|
|
|
