Product quality prediction in pulsed laser cutting of silicon steel sheet using vibration signals and deep neural network

Keyphrases

• Vibration Signal 100%
• Deep Neural Network 100%
• Product Quality Prediction 100%
• Pulsed Laser Cutting 100%
• Silicon Steel Sheet 100%
• Kerf Width 66%
• Wavelet Decomposition 33%
• Statistical Features 33%
• Selected Features 33%
• Straight Slot 33%
• Product Quality 16%
• Machining Parameters 16%
• K-best 16%
• Predictive Models 16%
• In(III) 16%
• Performance Comparison 16%
• Laser Machining 16%
• Feature Extracting 16%
• 3-axis 16%
• Pearson Correlation Coefficient 16%
• Five-level 16%
• Laser Cutting 16%
• Slot Cutting 16%
• Vibration Decomposition 16%
• Laser Cutting Machine 16%
• Raw Vibration Signal 16%
• Non-oriented Silicon Steel Sheet 16%

Engineering

• Product Quality 100%
• Electrical Steel 100%
• Pulsed Laser 100%
• Deep Neural Network 100%
• Network Model 50%
• Input Feature 50%
• Wavelet Decomposition 33%
• Statistical Feature 33%
• Time Domain 16%
• Machining Parameter 16%
• Input Data 16%
• Measured Signal 16%
• Extracted Feature 16%
• Pearsons Linear Correlation Coefficient 16%
• Axis Direction 16%

Material Science

• Laser Cutting 100%
• Silicon Steel 100%
• Steel Sheet 100%
• Laser Beam Machining 50%