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Three-dimensional instantaneous orbit map for rotor-bearing system based on a novel multivariate complex variational mode decomposition algorithm.
- Source :
-
Mechanical Systems & Signal Processing . Oct2022, Vol. 178, pN.PAG-N.PAG. 1p. - Publication Year :
- 2022
-
Abstract
- Full spectrum and holospectrum are homogeneous information fusion technology developed for the fault diagnosis of rotating machinery, which is extensively exploited in the analysis of the orbits of rotor-bearing systems. However, they are not adapted for non-stationary signals, nor can they be used for fusion analysis of vibrations of multiple bearing sections. By drawing inspiration from the multivariate variational mode decomposition (MVMD) and the complex-valued signal decomposition, we propose a method called multivariate complex variational mode decomposition (MCVMD). It can simultaneously extract the forward and backward components of multiple bearing sections and realize non-stationary complex signal decomposition of multiple bearing sections of the rotor. To achieve the visualization goal of condition monitoring, we propose the three-dimensional instantaneous orbit map (3D-IOM). It enables more features of shaft vibration of a rotor system to be displayed and offers a new way for the fusion analysis of vibration signals of multiple bearing sections of rotating machinery. Furthermore, making the most of the joint information, we also provide a high-resolution time-full spectrum (Time-FS) to display the forward and backward frequency components of multiple bearing sections. The effectiveness of the proposed method through both the simulated experiment and the real-life complex-valued signals is demonstrated in this paper. • A new multivariate complex variational mode decomposition method (MCVMD) is proposed. • 3D instantaneous orbit map is raised to visualize the instantaneous vibration state. • Time-FS, to integrate the frequency components into a TF plane, is devised. • The effectiveness is verified by the simulation test and real-world data. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 08883270
- Volume :
- 178
- Database :
- Academic Search Index
- Journal :
- Mechanical Systems & Signal Processing
- Publication Type :
- Academic Journal
- Accession number :
- 157221473
- Full Text :
- https://doi.org/10.1016/j.ymssp.2022.109211