Reliable multiple combined fault diagnosis of bearings using heterogeneous feature models and multiclass support vector Machines

Engineering

• Fault Diagnosis 100%
• Feature Model 100%
• Support Vector Machine 100%
• Feature Extraction 16%
• Classification Method 16%
• Test Sample 16%
• Decision Function 16%
• Acoustic Emission 16%
• Individual Support 16%
• Sample Space 16%
• Experimental Result 16%
• Classification Accuracy 16%
• Classification Performance 16%
• Time Domain 16%
• Feature Vector 16%
• Feature Space 16%
• Spatial Variation 16%
• Frequency Domain 16%
• Isolation Method 16%

Computer Science

• Support Vector Machine 100%
• Fault Diagnosis 100%
• Experimental Result 16%
• Classification Accuracy 16%
• Classification Performance 16%
• Individual Classifier 16%
• Frequency Domain 16%
• Feature Vector 16%
• Training Sample 16%
• Statistical Parameter 16%
• Final Decision 16%
• Dimensional Feature 16%
• Local Neighborhood 16%
• acoustic emission signal 16%
• Classification Method 16%
• Spatial Variation 16%
• Overlapped Feature Space 16%
• Feature Extraction 16%