Instantaneous frequency identification based on data-driven adaptive variational nonlinear chirp mode decomposition

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Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (20) : 18-25.

YUAN Pingping1，MAN Zhen2，ZHAO Zhoujie1，REN Weixin3

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Abstract

To reduce the impact of initial instantaneous frequency and signal noise on the variational nonlinear chirp mode decomposition (VNCMD), a data-driven adaptive variational nonlinear chirp mode decomposition (DDAVNCMD) is proposed in this paper. The modal number of the response signal is obtained by the proportion of modal energy, and the derivative normalization algorithm is used to preliminarily estimate the initial instantaneous frequencies of the modal components. An iterative time-varying filter is also added to reduce the noise effect. Based on this, the response signal is then subjected to VNCMD. The proposed method is validated through single-component and multi-component analytic signals, as well as a cable structure experiment. The research results indicate that the instantaneous frequency identification method based on DDAVNCMD has good accuracy and anti-noise performance.

Key words

instantaneous frequency / variational nonlinear chirp mode decomposition (VNCMD) / derivative normalization / iterative time-varying filter / data-driven adaptive variational nonlinear chirp mode decomposition (DDAVNCMD)

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YUAN Pingping1, MAN Zhen2, ZHAO Zhoujie1, REN Weixin3. Instantaneous frequency identification based on data-driven adaptive variational nonlinear chirp mode decomposition[J]. Journal of Vibration and Shock, 2024, 43(20): 18-25

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