Active noise control (ANC) is an effective method to suppress vehicle road noise. The rapid selection of the reference sensor set and rational selection of its layout position are crucial for determining the vibration noise transmission paths with high contributions, which determines the noise reduction performance of the active road noise control (ARNC) system. The reference sensor set selected by the conventional multiple coherence function (MCOH) method does not always ensure the optimal noise reduction performance and the matrix singularity problem based on the Fisher information matrix (FIM) expansion method. To alleviate this problem, this paper proposes a method based on the overall level of noise reduction (OANR) and the FIM to select a set of reference sensors and determine their positions. This method uses an optimal causally constrained Wiener filter to estimate the theoretical OANR for each control area to ensure the reference sensor selected has the optimal noise reduction performance, and it expands efficiently based on the FIM method to select a set of reference sensors. Besides, the matrix singularity problems in the FIM-based expansion method are solved using noise frequency summation and matrix operation, which makes the method more universally applicable. Numerical simulations are performed to analyze and evaluate the noise reduction performance and selection efficiency of the proposed method under different conditions. In addition, a series of real vehicle ANC experiments are conducted. The results show that the reference sensor set selected based on the proposed method has an obvious advantage in noise reduction performance, and only four reference sensors are needed to achieve 4.63 dB(A) noise reduction in ARNC experiments. It fully confirms the effectiveness of the proposed method in real vehicle applications

中文翻译：

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基于降噪估计的道路噪声主动控制传感器优化布局方法


主动噪声控制（ANC）是抑制车辆道路噪声的有效方法。参考传感器组的快速选择及其布局位置的合理选择对于确定贡献较大的振动噪声传播路径至关重要，这决定了主动道路噪声控制（ARNC）系统的降噪性能。传统的多重相干函数（MCOH）方法选择的参考传感器组并不总能保证最优的降噪性能以及基于Fisher信息矩阵（FIM）展开方法的矩阵奇异性问题。为了缓解这个问题，本文提出了一种基于总体降噪水平（OANR）和FIM的方法来选择一组参考传感器并确定它们的位置。该方法使用最优因果约束维纳滤波器来估计每个控制区域的理论OANR，以确保所选的参考传感器具有最优的降噪性能，并在FIM方法的基础上进行有效扩展以选择一组参考传感器。此外，利用噪声频率求和和矩阵运算解决了基于FIM的展开方法中的矩阵奇异性问题，使得该方法具有更广泛的适用性。通过数值模拟分析和评估该方法在不同条件下的降噪性能和选择效率。此外，还进行了一系列实车ANC实验。结果表明，基于该方法选择的参考传感器组在降噪性能方面具有明显优势，在ARNC实验中仅需要四个参考传感器即可实现4.63 dB(A)的降噪效果。充分证实了该方法在实车应用中的有效性