Three-dimensional instantaneous orbit map for rotor-bearing system based on a novel multivariate complex variational mode decomposition algorithm

TL;DR

This paper introduces a novel multivariate complex variational mode decomposition method for analyzing non-stationary rotor-bearing vibrations, enabling detailed visualization and fusion analysis of signals from multiple bearing sections.

Contribution

It proposes the MCVMD algorithm and 3D-IOM visualization technique, advancing fault diagnosis by handling complex, multi-section vibration signals more effectively.

Findings

Successfully decomposed non-stationary signals from multiple bearings.

Enhanced visualization of rotor vibrations through 3D orbit maps.

Validated effectiveness with simulated and real signals.

Abstract

Full spectrum and holospectrum are homogenous 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.