Structural modal parameter identification method

Abstract

The invention relates to a structural modal parameter identification method used for identification of modal frequency, damping and vibration mode of civil and space structures. The method comprises the following steps: carrying out experience mode decomposition on a noisy vibration testing signal of a structure, and carrying out power spectrum analysis on an obtained intrinsic mode function component after decomposition; according to a frequency structure of each intrinsic mode function component, selecting an intrinsic mode function component containing structural modal information, and carrying out linear superposition to obtain a reconstruction signal; utilizing the reconstruction signal to carry out Morlet wavelet transformation, carrying out least square linear fitting on instantaneous amplitude logarithm and phase of a wavelet transformation coefficient corresponding to each modal, and calculating modal frequency, modal damping and modal vibration mode of the structure.

Description

【Technical field】 [0001] The patent of the present invention relates to a structural modal parameter identification method, more specifically, to a structural modal parameter identification method based on empirical mode decomposition and Morlet wavelet transform, which is used for modal frequency, Damping and identification of mode shapes. 【Background technique】 [0002] Empirical mode decomposition and wavelet transform techniques for identifying modal frequencies, damping, and mode shapes of civil and aerospace structures are well known in the prior art, but existing similar methods generally perform empirical mode decomposition on structural vibration test signals A series of eigenmode function components are obtained, and then Hilbert transform or wavelet transform is performed on a single eigenmode function, and then the modal parameters are identified. A major drawback of these methods is that they can only target impulse response signals with relatively good signal-...

AI Technical Summary

Problems solved by technology

Since the empirical mode decomposition has relatively high requirements on the signal, the eigenmode function components decomposed by a little noise are not ideal, and the clear vibration mode meaning is lost.

Although band-pass filtering is used in similar methods to alleviate this problem, the obtained eigenmode function components are still prone to modal aliasing. When the ratio is not high, it is often unsuccessful, and the modal parameters of the structure cannot be identified

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