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OPTIMAL EIGENVECTORS DESIGN FOR STRUCTURAL NOISE REDUCTION THROUGH ADAPTIVE SANDWICH ALGORITHM

机译:通过自适应三明治算法实现结构降噪的最佳特征向量

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The purpose of this research is to investigate the feasibility of utilizing the adaptive sandwich algorithm to find the optimal left and right eigenvectors for active structural noise reduction. As depicted in the previous studies, the structural acoustic radiation depends on the structural vibration behavior, which is strongly related to both the left eigenvectors (concept of disturbance rejection capability) and right eigenvectors (concept of mode shape distributions) of the system, respectively. In this research, a novel adaptive sandwich algorithm is developed for determining the optimal combination of left and right eigenvectors of the structural system. The sound suppression performance index (SSPI) is defined by combining the orthogonality index of left eigenvectors and the modal radiation index of right eigenvectors. Through the proposed adaptive sandwich algorithm, both the left and right eigenvectors are adjusted such that the SSPI decreases, and therefore one can find the optimal combination of left and right eigenvectors of the closed-loop system for structural noise reduction purpose. The optimal combination of left-right eigenvectors is then synthesized to determine the feedback gain matrix of the closed-loop system. The result of the active noise control shows that the proposed method can significantly suppress the sound pressure radiated from the vibrating structure.
机译:本研究的目的是研究利用自适应三明治算法找到最佳左右特征向量,用于有源结构降噪。如先前的研究中所示,结构声辐射取决于结构振动行为,其与系统的左特征向量(扰动抑制能力概念)和右特征向量(模式形状分布的概念)密切相关。在该研究中,开发了一种新的自适应三明治算法,用于确定结构系统的左右特征向量的最佳组合。通过组合左特征向量的正交性索引和右特征向量的模态辐射指数来定义声音抑制性能指数(SSPI)。通过所提出的自适应三明治算法,调整左和右特征向量,使得SSPI降低,因此可以找到闭环系统的左右特征向量的最佳组合,以实现结构降噪。然后合成左右特征向量的最佳组合以确定闭环系统的反馈增益矩阵。有源噪声控制的结果表明,所提出的方法可以显着地抑制从振动结构辐射的声压。

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