一个在线解-变白频域过-错误最小平均平方算法,用于积极的道路噪声控制
Siyuan Lian1,2, Tianyou Li1,2, Jincheng Gu2
1Key Laboratory of Modern Acoustics, Institute of Acoustics, Nanjing University, Nanjing 210093, China.
积极道路噪声控制 (ARNC) 系统可以通过新算法进行改进. ODW-FDFeLMS算法提供更快的融合和更低的计算成本,以有效地降低车噪声.
科学领域:
- 声学 声学 在声学方面
- 信号处理 信号处理
- 汽车工程 汽车工程
背景情况:
- 积极道路噪声控制 (ARNC) 系统旨在减少车辆内的低频噪声.
- 现有的系统往往需要多个传感器,导致更慢的融合和更高的计算负载.
- 挑战包括在自适应算法中的二次路径合和参考信号相关性.
研究的目的:
- 提出一种新的算法,用于加强道路活动噪声控制.
- 为了解决现有的ARNC算法的局限性,特别是融合速度和计算复杂性.
- 改进ARNC系统在车辆中的实际实施.
主要方法:
- 引入了一种在线解-美白频率域过-错误最小平均平方 (ODW-FDFeLMS) 算法.
- 通过内外产品分解实现了二次路径脱.
- 在线参考白化是使用光谱因子化进行的.
- 频域处理和过错误方法减少了计算复杂性.
主要成果:
- 与现有算法相比,模拟显示出更高的融合速度和更低的计算复杂性.
- 在车中的实时实验验证实了ODW-FDFeLMS算法的有效性.
- 拟议的方法显著提高了ARNC的性能.
结论:
- 该ODW-FDFeLMS算法有效地克服了传统ARNC方法的局限性.
- 该算法提供了一种实用且高效的解决方案,用于实时控制车辆的道路噪音.
- 这一进步有助于通过优异的降噪来提高车舒适度.
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