Fault Diagnosis of Wind Energy Conversion Systems Using Gaussian Process Regression-based Multi-Class Random Forest

Keyphrases

• Gaussian Process Regression 100%
• Regression-based Method 100%
• Fault Diagnosis 100%
• Wind Energy Conversion System 100%
• Multi-class Random Forests 100%
• Random Forest Method 50%
• Feature Extraction 33%
• State-of-the-art Techniques 16%
• Diagnostic Accuracy 16%
• Statistical Features 16%
• Data-centric 16%
• Short-circuit Fault 16%
• Forest-based 16%
• Diagnosis Approach 16%
• Effective Feature 16%
• Open Circuit 16%
• Mean Vector 16%
• New Fault 16%
• Fault Classification 16%
• Wearout 16%
• Variance Matrix 16%
• RF Classifier 16%

Engineering

• Gaussians 100%
• Random Forest 100%
• Fault Diagnosis 100%
• Wind Energy Conversion System 100%
• Feature Extraction 16%
• Based Feature Extraction 16%
• Illustrates 16%
• State-of-the-Art Method 16%
• Circuit Faults 16%
• Open Circuit 16%
• Statistical Feature 16%
• Raw Data 16%
• Effective Feature 16%

Computer Science

• Random Decision Forest 100%
• Fault Diagnosis 100%
• Feature Extraction 33%
• Case Study 16%
• Statistical Feature 16%
• Variance Matrix 16%