A sparse approach to fault severity classification for gearbox monitoring

Engineering

• Gearbox 100%
• Raw Data 50%
• Sensor Data 50%
• Good Performance 25%
• Test Rig 25%
• Classification Accuracy 25%
• Extracted Feature 25%
• Structural Health Monitoring 25%
• Signal Level 25%
• Mapping Vector 25%
• Partial Information 25%
• Covariance Matrix 25%
• Fault Detection 25%

Computer Science

• Sparse Representation 100%
• Data Fusion 66%
• classification result 33%
• Structural Health 33%
• Covariance Matrix 33%
• Good Performance 33%
• Extracted Feature 33%
• Classification Accuracy 33%
• Level Classifier 33%
• Fault detection 33%