噪音(视频)
噪音、振动和粗糙度
连贯性(哲学赌博策略)
严厉
计算机科学
控制理论(社会学)
降噪
振动
还原(数学)
工程类
噪声控制
电子工程
声学
人工智能
数学
控制(管理)
物理
图像(数学)
统计
几何学
作者
Yun Seol Park,Mun Hwan Cho,Chi Sung Oh,Yeon June Kang
标识
DOI:10.1016/j.ymssp.2021.108788
摘要
Road noise is the dominant noise source that directly affects the vehicle noise, vibration, and harshness (NVH) performance. The active noise control (ANC) technology is a promising solution for reducing interior noise from tire–road interactions. Active road noise control (ARNC) systems include a set of acceleration sensors, which acquire vibrations that cause road noise, and the locations of the sensors is important to accurately determine the vibration transfer path. Therefore, it is necessary to find an optimal sensor set among the candidate sensors to maximize the performance of the ARNC system. The trial-and-error method for simulating all possible sensor combinations requires a high computational cost. This paper proposes a method that determines the set of reference sensor locations with the coherence analysis and the Fisher information matrix. The methodology starts with one sensor highly correlated with the output sound pressure level signals. The initial sensor set is iteratively expanded to the desired number of sensors by maximizing the determinant of the coherence information matrix. This approach can significantly reduce the amount of computation and subsequently shorten the time required. In addition, the obtained local optimal results indicated a reduction in broadband road noise of approximately 7 dBA and showed an error within 0.2 △dBA of the targeted noise reduction results in all driving conditions.
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