Partial Discharge Severity Classification for Transformer Condition Monitoring Using Feature Engineering, PCA, and ANN

Keyphrases

• Principal Coordinate Analysis (PCoA) 100%
• Artificial Neural Network 100%
• Feature Engineering 100%
• Partial Discharge 100%
• Severity Classification 100%
• Transformer Condition Monitoring 100%
• Feature Space 60%
• Severity Class 40%
• Applied Voltage 20%
• Total Variance 20%
• Multilayer Perceptron 20%
• Artificial Neural Network Model 20%
• Support Vector Machine 20%
• Multilayer Perceptron Neural Network (MLPNN) 20%
• Nave Bayes 20%
• Neighborhood Support 20%
• Ratio-based 20%
• Energy-based 20%
• Test Accuracy 20%
• Diagnostic Performance 20%
• Classification Framework 20%
• Transformer 20%
• 5-fold Cross Validation 20%
• Overfitting 20%
• Bayes Model 20%
• Feature Dimension 20%
• Insulation Degradation 20%
• K-nearest 20%
• Classification Basis 20%
• IEC 60270 20%
• Engineered Features 20%
• Partial Discharge Activity 20%
• High-frequency Transformer 20%
• High Severity 20%
• Partial Discharge Detection 20%
• Raw Measurements 20%
• Transformer Partial Discharge 20%
• Normalized Features 20%
• Physics-informed Feature 20%
• Partial Discharge Magnitude 20%
• Electrical Measurement Method 20%
• Incipient Failure 20%

Engineering

• Component Analysis 100%
• Condition Monitoring 100%
• Principal Components 100%
• Artificial Neural Network 100%
• Feature Engineering 100%
• Feature Space 28%
• Perceptron 28%
• Artificial Neural Network Model 14%
• Dimensionality 14%
• Applied Voltage 14%
• Gaussians 14%
• Support Vector Machine 14%
• Nearest Neighbor 14%
• Electrical Measurement 14%
• Measurement Method 14%
• Voltage Transformer 14%
• Dimensional Feature Space 14%

Chemical Engineering

• Condition Monitoring 100%
• Neural Network 100%
• Multilayer Neural Networks 50%
• Support Vector Machine 25%