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首页> 外文期刊>Mechanical Engineering Journal >Road & wind noise contribution separation using only interior noise having multiple sound sources -Accuracy improvement and permutation solution-
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Road & wind noise contribution separation using only interior noise having multiple sound sources -Accuracy improvement and permutation solution-

机译:仅使用具有多个声源的内部噪声来分离道路和风噪声贡献-精度提高和置换解决方案-

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摘要

A contribution separation technique for estimating road noise and wind noise contributions to vehicle interior noise without using any sound source information was considered when each noise was from multiple sources. In the test, road, wind or mixed noise sources were reproduced from four speakers placed at different positions. The mixed interior noises were recorded at two separate positions surrounded by the speakers. Independent component analysis (ICA) was then applied as the contribution separation method for obtaining them at the target position (driver seat position). As the original condition, ICA was firstly applied to the recorded noises at the driver seat (target noise) and at the assistant seat (reference noise). The result revealed that the estimated contribution was inaccurate due to the low accuracy at the low frequency and the permutation problem, in which the relationship between the calculated contribution and the actual contributions is not retained with changes in frequency. Next, the reference signal was changed to the other noise having lower correlation to the target for improvement of the accuracy and the permutation solution was considered by using the time trend correlation of the calculated contributions of dominant independent component. The modified ICA technique with the permutation solution could estimate more accurate contributions than the original condition.
机译:当每种噪声来自多个源时,考虑使用一种贡献分离技术来估计道路噪声和风噪声对车辆内部噪声的影响,而无需使用任何声源信息。在测试中,从放置在不同位置的四个扬声器复制了道路,风或混合噪声源。混合的内部噪音记录在扬声器环绕的两个单独位置。然后应用独立成分分析(ICA)作为贡献分离方法,以在目标位置(驾驶员座椅位置)获得它们。作为原始条件,首先将ICA应用于驾驶员座椅和辅助座椅上的记录噪音(目标噪音)。结果表明,由于低频处的精度低和排列问题,估计的贡献是不准确的,其中,随着频率的变化,计算的贡献和实际贡献之间的关系并未得到保留。接下来,将参考信号改变为与目标具有较低相关性的另一噪声以提高精度,并且通过使用所计算的主要独立分量的贡献的时间趋势相关性来考虑置换解。带有置换解决方案的改进的ICA技术可以估计比原始条件更准确的贡献。

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