The Application of Risk Minimization to the Selection of Fiber Optic Sensors for an Aerospace Structural Monitoring Application

Keyphrases

• Risk Minimization 100%
• Aerospace 100%
• Optical Fiber Sensor 100%
• Damage Parameter 100%
• Structural Health Monitoring 100%
• Monitoring Applications 100%
• Buckling Eigenvalues 100%
• Structural Monitoring 100%
• Utility Function 50%
• Finite Element Model 50%
• Composite Materials 50%
• Machine Learning Techniques 50%
• False Alarm Rate 50%
• Debonding 50%
• Strain Measurement 50%
• Bayesian Inference 50%
• Detection Probability 50%
• High Computational Cost 50%
• Data Acquisition System 50%
• Biaxial Strain 50%
• Surrogate Model 50%
• Local Buckling 50%
• Structural Loads 50%
• Number of Sensors 50%
• Sensor Placement 50%
• Sensor Location 50%
• Physics-based Model 50%
• Health Monitoring Applications 50%
• Structural Health Monitoring System 50%
• Optimal Sensor Placement 50%
• Load Capability 50%
• Wing Spar 50%
• Load Damage 50%
• Synthetic Data Generator 50%
• Debonding Damage 50%
• Bayesian Optimization 50%
• Aircraft Wing 50%
• Hardware Sensors 50%
• Sensor Data Collection 50%

Engineering

• Fiber Optic Sensor 100%
• Structural Health Monitoring 100%
• Application Monitoring 100%
• Eigenvalue 66%
• Buckling 66%
• Debonding 66%
• Damage Parameter 66%
• Objective Function 33%
• Finite Element Modeling 33%
• Composite Material 33%
• Computational Cost 33%
• Machine Learning Method 33%
• Sensor Data 33%
• Measured Strain 33%
• Data Acquisition System 33%
• Surrogate Model 33%
• Local Buckling 33%
• Structural Load 33%
• Probability of False Alarm 33%
• Location Sensor 33%
• Probability of Detection 33%
• Health Monitoring System 33%
• Wings 33%