A new compound faults detection method for rolling bearings based on empirical wavelet transform and chaotic oscillator
- 9 October 2015
- journal article
- Published by Elsevier BV in Chaos, Solitons, and Fractals
- Vol. 89, 8-19
- https://doi.org/10.1016/j.chaos.2015.09.007
Abstract
No abstract availableKeywords
This publication has 23 references indexed in Scilit:
- Integration of EEMD and ICA for wind turbine gearbox diagnosisWind Energy, 2013
- A review on empirical mode decomposition in fault diagnosis of rotating machineryMechanical Systems and Signal Processing, 2013
- Basic Research on Machinery Fault Diagnosis—What is the PrescriptionJournal of Mechanical Engineering, 2013
- Synchrosqueezed wavelet transforms: An empirical mode decomposition-like toolApplied and Computational Harmonic Analysis, 2011
- Rolling element bearing diagnostics—A tutorialMechanical Systems and Signal Processing, 2011
- Enhancement of signal denoising and multiple fault signatures detecting in rotating machinery using dual-tree complex wavelet transformMechanical Systems and Signal Processing, 2010
- Separation and Extraction of Electromechanical Equipment Compound Faults Using Lifting MultiwaveletsJournal of Mechanical Engineering, 2010
- Support vector machine in machine condition monitoring and fault diagnosisMechanical Systems and Signal Processing, 2007
- Detection and Sorting of Neural Spikes Using Wavelet PacketsPhysical Review Letters, 2000
- Brushlets: A Tool for Directional Image Analysis and Image CompressionApplied and Computational Harmonic Analysis, 1997