Bearing Fault Detection Based on SVD and EMD

Yan Long Chen; Pei Lin Zhang

doi:10.4028/www.scientific.net/AMM.184-185.70

Paper Titles

An Experimental Study of V-Ring Position on the Die Roll Height in the Fine Blanking of Special Part with Corner Shapes
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An Improved Damage Detection Method and its Application
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Analysis of Dry Dual Clutch Transmission Technology
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Applied Research on Optimum Design of Planetary Reducer
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Bearing Fault Detection Based on SVD and EMD
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Bending Analysis and Measures of the Forming of Automobile Semi-Axle on Cross-Wedge Rolling with Multi-Wedge
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Calculation of Rigid-Body Motion of Integrated Raft Isolation System
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CFD Prediction of the Effects of Surface Roughness on Elastohydrodynamic Lubrication under Rolling/Sliding Conditions
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Comparative Analysis of HPDC Process of an Auto Part with ProCAST and FLOW-3D
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 184-185Bearing Fault Detection Based on SVD and EMD

Bearing Fault Detection Based on SVD and EMD

Abstract:

While bearing fault signals are strongly interferenced by noise, diagnosis using EMD directly for bearings fault becomes incorrect. A scheme based on Singular Value Decomposition(SVD) and Empirical Mode Decomposition(EMD) is proposed for solving this problem. Aiming at bearing fault signal characteristics, SVD preprocesses sampled signals to denoise. Then preprocessed signals are analyzed by EMD. Fault characteristic frequency can be obtained by spectrum analysis for Intrinsic Mode Functions(IMFs). This method is useful to detect fault of bearings and a comparison is made between it and EMD. The results show that this scheme can diagnose fault correctly under strong noise.