A Vibration-Based Machine Learning Approach for Roller Gap Detection in Biomass Pellet Production

Keyphrases

• Machine Learning Approach 100%
• Roller 100%
• Biomass Pellets 100%
• Pellet Production 100%
• Vibration-based Method 100%
• Gap Detection 100%
• Response Surface Model 60%
• Experimental Testing 40%
• Significant Relationship 20%
• Valuable Insight 20%
• Machine Learning 20%
• Mathematical Model 20%
• Comprehensive Approach 20%
• Product Quality 20%
• Process Dynamics 20%
• F1 Score 20%
• Machine Learning Techniques 20%
• Coefficient of Determination 20%
• Quality Metrics 20%
• Manufacturing Process 20%
• Biomass Industry 20%
• Optimization Criterion 20%
• Pellet Quality 20%
• Rotary 20%
• Optimization Efficiency 20%
• Ring Die 20%
• Process Metrics 20%
• Machine Learning Model Performance 20%
• Pellet Mill 20%
• Surface Vibration 20%

Engineering

• Learning Approach 100%
• Response Surface 100%
• Surface Modeling 100%
• Biomass Pellet 100%
• Learning System 100%
• Metrics 66%
• Product Quality 33%
• Optimal Condition 33%
• Manufacturing Process 33%
• Machine Learning Technique 33%
• Process Dynamic 33%
• Process Variable 33%
• Mathematical Model 33%

Chemical Engineering

• Learning System 100%
• Pelletizing 50%