Physics-guided neural network for grinding temperature prediction

Keyphrases

• Temperature Prediction 100%
• Physics-informed Neural Networks 100%
• Grinding Temperature 100%
• Data-driven Model 40%
• Prediction Accuracy 20%
• Physical Model 20%
• Performance Prediction 20%
• Processing Speed 20%
• Training Data 20%
• Noisy Data 20%
• Processing Temperature 20%
• Number of Experiments 20%
• Process Optimization 20%
• Quality Issues 20%
• Experiment Results 20%
• Accurate Model 20%
• Small Sample Size Problem 20%
• Loss Function 20%
• Network Training 20%
• Small Sample Set 20%
• Data Augmentation 20%
• Grinding Experiment 20%
• Temperature Limitation 20%
• Physics-guided 20%
• Processing Quality 20%
• High Efficiency 20%
• Experimental Dataset 20%
• Precision Grinding Process 20%
• Neural Network Structure Optimization 20%
• Creep Feed Grinding 20%
• Aviation Engine 20%

Engineering

• Grinding (Machining) 100%
• Quality Issue 14%
• Prediction Performance 14%
• Network Training 14%
• Temperature Limit 14%
• Noisy Data 14%
• Creep 14%
• Limitations 14%
• Physical Model 14%
• Loss Function 14%