The determination of the number of active modes is always an obstacle to the identification of dynamic systems. To tackle this issue, a new blind modal estimation method is proposed through which the number of active modes does not need to be presupposed, even in underdetermined blind source separation cases. Firstly, the spatial time–frequency distribution matrices are constituted from the smoothed pseudo Wigner–Ville distribution of acceleration signals. The auto-source time–frequency points that contain modal information about only one mode are selected and then the density peaks clustering algorithm is introduced to identify the mode shape vectors. Finally, one can reconstruct the time–frequency distributions of modal coordinates and estimate the natural frequencies and damping ratios. The method is verified by a numerical study and a vibration experiment. The anti-noise study demonstrates that the method performs well.

中文翻译：

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使用平滑伪Wigner-Ville分布和密度峰聚类的盲模态估计

确定活动模式的数量始终是识别动态系统的障碍。为了解决这个问题，提出了一种新的盲模态估计方法，通过该方法，即使在不确定的盲源分离情况下，也不需要预先设定有效模态的数量。首先，由加速信号的平滑伪Wigner-Ville分布构成空间时频分布矩阵。选择仅包含一种模式的模态信息的自动源时频点，然后引入密度峰聚类算法以识别模式形状矢量。最后，可以重建模态坐标的时频分布，并估计固有频率和阻尼比。通过数值研究和振动实验验证了该方法。抗噪声研究表明该方法性能良好。