Enhanced fault diagnosis of roller bearing elements using a combination of empirical mode decomposition and minimum entropy deconvolution

Keyphrases

• Fault Diagnosis 100%
• Empirical Mode Decomposition 100%
• Bearing Elements 100%
• Minimum Entropy Deconvolution 100%
• Roller Bearing 100%
• Energy Moment 75%
• Fault Detection 50%
• Moment Technique 50%
• Processing Chain 50%
• Feature Identification 25%
• Improved Technique 25%
• Decomposition Process 25%
• Laboratory Testing 25%
• Minimum Entropy 25%
• Signal Processing Algorithms 25%
• Roller 25%
• Feature Selection 25%
• Deconvolution Method 25%
• First Mode 25%
• New Signals 25%
• Automatic Features 25%
• Noise Signal 25%
• Automatically Identify 25%
• Intrinsic Mode Function 25%
• Selection Stages 25%
• Energy Method 25%
• Traditional Energy 25%
• Moment Approach 25%
• Empirical Mode 25%
• Empirical Mode Decomposition Algorithm 25%
• Outer Race Defect 25%
• Roller Bearing Fault 25%
• Non-stationary Conditions 25%
• Deconvolution Approach 25%
• Adaptive Technique 25%
• Tapered Roller Bearing 25%
• Vibration-based Fault Detection 25%
• Identification Mechanism 25%
• Data-adaptive 25%

Engineering

• Fault Diagnosis 100%
• Empirical-Mode Decomposition 100%
• Deconvolution 100%
• Bearing Element 100%
• Early Stage 40%
• Fault Detection and Diagnosis 40%
• Experimental Result 20%
• Decomposition Process 20%
• Feature Extraction 20%
• Intrinsic Mode Function 20%
• Processing Algorithm 20%
• Identification Mechanism 20%
• Stationary Condition 20%
• Noise Scenario 20%
• Tapered Roller Bearings 20%
• Noisy Signal 20%