Fault detection of gearbox by multivariate extended variational mode decomposition-based time-frequency images and
1Medical Technology School, Qiqihar Medical University, Qiqihar, 161000, China.
Abstract:
A novel detection method based on multivariate extended variational mode decomposition-based time-frequency images and incremental RVM algorithm (MEVMDTFI-IRVM) is presented for fault detection of gearbox. The time-frequency images are constructed by multivariate extended variational mode decomposition. Compared with single-variable modal decomposition method, multivariate extended variational mode decomposition not only has an accurate mathematical framework, but also has good robustness to non-stationary multi-channel signals with low signal-to-noise ratio. The incremental RVM algorithm is presented for fault detection of gearbox based on the time-frequency images constructed by multivariate extended variational mode decomposition. The testing results demonstrate that the detection results of MEVMDTFI-IRVM for gearbox are stable, in addition, the detection results of MEVMDTFI-IRVM for gearbox are better than those of variational mode decomposition-based time-frequency images and incremental RVM algorithm (VMDTFI-IRVM), variational mode decomposition-RVM algorithm (VMD-RVM), and traditional RVM algorithm.
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