A Developed Convolutional Neural Network Architecture for Condition Monitoring

Mathematics

• Architecture 61%
• Condition Monitoring 100%
• Cover 6%
• Demonstrate 5%
• Diagnostic Accuracy 14%
• Fault Diagnosis 29%
• Feature Extraction 41%
• Filter 16%
• Form 3%
• High Accuracy 9%
• Learning 8%
• Model 6%
• Multilayer 11%
• Network Architecture 85%
• Network Performance 15%
• Neural Networks 52%
• Time series 8%
• Vibration 35%

Business & Economics

• Condition Monitoring 87%
• Deep Learning 19%
• Diagnostics 13%
• Fault Diagnosis 47%
• Feature Extraction 65%
• Filter 29%
• Learning Model 21%
• Neural Networks 67%
• Performance 5%
• Train 13%
• Vibration 77%

Engineering & Materials Science

• Condition monitoring 58%
• Convolutional neural networks 51%
• Deep learning 16%
• Failure analysis 32%
• Feature extraction 43%
• Multilayers 18%
• Network architecture 52%
• Network performance 18%
• Time series 16%