Reliable bearing fault diagnosis using Bayesian inference-based multi-class support vector machines

Engineering

• Gaussians 100%
• Prior Process 100%
• Rolling Element 100%
• Feature Space 100%
• Support Vector Machine 100%
• Bearing Fault Diagnosis 100%
• Fault Diagnosis 50%
• Pattern Recognition 50%
• Acoustic Emission 50%
• Experimental Result 50%
• Classification Accuracy 50%
• Time Domain 50%
• Frequency Domain 50%
• Probability Estimation 50%
• Posterior Probability 50%
• Data Sample 50%
• Estimation Procedure 50%

Computer Science

• Support Vector Machine 100%
• Fault Diagnosis 100%
• Experimental Result 14%
• Classification Accuracy 14%
• Feature Space 14%
• wavelet packet transform 14%
• acoustic emission signal 14%
• binary classifier 14%
• Probability Estimation 14%
• Overlapped Feature Space 14%
• Estimation Procedure 14%
• Posterior Probability 14%
• Pattern Recognition 14%