A survey of transfer learning for machinery diagnostics and prognostics

Keyphrases

• Transfer Learning 100%
• Machinery Diagnostics 100%
• Machinery Prognostics 100%
• Data-driven Methods 40%
• Transfer Learning Models 40%
• Main Idea 20%
• Data-driven Modeling 20%
• System Failure 20%
• Comprehensive Survey 20%
• System Reliability 20%
• Mechanical Components 20%
• Labeled Data 20%
• Industrial Production Systems 20%
• Transfer Method 20%
• Operation Conditions 20%
• Operational System 20%
• High Performance Data 20%
• Feature Matching 20%
• Data Accuracy 20%
• Transfer Parameters 20%
• Adversarial Adaptation 20%
• Emerging Challenges 20%
• Recent Research Progress 20%
• Safety Reliability 20%
• Method Transfer 20%
• Operational Safety 20%
• Typical Model 20%
• Parameter Transfer 20%
• Model Transfer 20%
• Industrial Applications 20%
• Model Generalization 20%
• Feature Adversarial 20%
• Cross-domain Transfer Learning 20%

Engineering

• Transfer Learning 100%
• Industrial Applications 20%
• System Reliability 20%
• Performance Data 20%
• Gas Fuel Manufacture 20%
• Accident Prevention 20%
• Mechanical Component 20%

Computer Science

• Transfer Learning 100%
• Open Source 20%
• Research Direction 20%
• Performance Data 20%
• Industrial Applications 20%