关键词: 改进EEMD算法, 模态辨识, 希尔伯特变换, 模态混叠, 端点效应

Abstract:

The key to improving the accuracy of vibration mode identification is to improve the separation accuracy of dense natural modes. Based on the analysis of the sieving results of ensemble empirical mode decomposition （EEMD）， this paper proposes a multi-noise method. The improved sieving algorithm， combined with the Hilbert Transform（HT） method， is applied to the identification of missile operating modes. Compared with the sieving results of empirical mode decomposition and ensemble empirical mode decomposition algorithms， the new algorithm reduces the error and effectively suppresses the phenomenon of modal aliasing. Compared with the logarithmic decay method， the Hilbert transform is used for mode identification， which improves the parameter identification accuracy， and can identify the variation law of natural frequency with time， which is more suitable for analyzing the time-varying missile working mode. This research can provide a reference for solving the modal aliasing problem in signal processing.

Key words: improved ensemble empirical mode decomposition（EEMD） algorithm, mode identification, Hilbert transform, modes aliasing, end effect