Development of machine learning based classifier for the pressure test result prediction of type IV composite overwrapped pressure vessels

Keyphrases

• Pressure Test 100%
• Machine Learning Classifiers 100%
• Composite Overwrapped Pressure Vessel 100%
• TabNet 100%
• Result Prediction 100%
• XGBoost 50%
• Cycling Test 50%
• Pressure Cycling 50%
• Burst Pressure 50%
• Classification Accuracy 25%
• Statistical Features 25%
• Classification Results 25%
• Training Process 25%
• Decision Tree 25%
• Logistic Regression 25%
• Commercial Application 25%
• Safety Test 25%
• Acoustic Emission 25%
• Emission Data 25%
• Commercial Vehicle 25%
• Safety Regulation 25%
• Structure Health Monitoring 25%
• Naïve Bayes 25%
• Certification Process 25%
• Damage Prediction 25%
• Pressurization 25%
• Regression Decision Trees 25%
• Health Damage 25%
• Proof Test 25%
• Burst Pressure Test 25%
• Feature Sensitivity 25%
• Damage State 25%

Engineering

• Test Result 100%
• Learning System 100%
• Pressure Vessel 100%
• Burst Pressure 75%
• Collected Data 50%
• Xgboost 50%
• Damage State 25%
• Test Data 25%
• Classification Accuracy 25%
• Statistical Feature 25%
• Safety Test 25%
• Pressurization 25%
• Safety Regulation 25%
• Commercial Vehicle 25%
• Acoustic Emission 25%
• Health Monitoring 25%

Chemical Engineering

• Learning System 100%
• Xgboost 66%