NDLI: An inverse decaying frequency modulation EMD method for closely spaced modal parameter identification in high precision with Laplace wavelet correlation filtering

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An inverse decaying frequency modulation EMD method for closely spaced modal parameter identification in high precision with Laplace wavelet correlation filtering

Content Provider	Scilit
Author	Zhang, Xiaoli Yang, Ji Wang, Baojian Yan, Qiang Zhang, Han
Copyright Year	2020
Description	Journal: Measurement Science and Technology Modal parameter identification is a useful tool to reveal natural vibration characteristics in dynamic design and analysis. Due to the influence of closely spaced modes with close frequencies and large dampings, the identification accuracy with traditional Hilbert-Huang Transform (HHT) is always unsatisfactory since the deadline requirement of neighboring intrinsic mode functions (IMFs) cannot be satisfied when the frequency ratio (high frequency versus low frequency) of two adjacent modes is less than two. Therefore, an inverse decaying frequency modulation empirical mode decomposition (IDFM-EMD) method is proposed to separate multiple closely spaced modes in high precision, which not only adjusts the frequency ratio by frequency modulation but also decreases the damping by inverse decaying simultaneously. Then, the modal parameters of each separated single mode are picked up by Laplace wavelet correlation filtering. The effectiveness of the proposed method is validated by simulated signals in noise and noise-free conditions in contrast with other methods, showing advantages in high precision of closely spaced mode identification. In addition, the proposed method is applied in assembly tightness identification of bolts in an aero-engine rotor, which achieves successful results.
Related Links	https://iopscience.iop.org/article/10.1088/1361-6501/ab8cfe/pdf
ISSN	09570233
e-ISSN	13616501
DOI	10.1088/1361-6501/ab8cfe
Journal	Measurement Science and Technology
Issue Number	10
Volume Number	31
Language	English
Publisher	IOP Publishing
Publisher Date	2020-04-24
Access Restriction	Open
Subject Keyword	Journal: Measurement Science and Technology Industrial Relations Wavelet Correlation Filtering Laplace Wavelet Correlation
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Instrumentation Engineering

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