Bayesian Tendon Break Localization under Model Uncertainty Using Distributed Fiber Optic Sensors

Key Points

• The research aims to enhance tendon break detection by applying Bayesian methods in the context of model uncertainty.
• Utilized a Bayesian framework to analyze tendon break data.
• Implemented distributed fiber optic sensors for data collection.
• Conducted analysis in a Linux environment using a specified installation script.
• Successfully localized tendon breaks in the presence of model uncertainty.
• Demonstrated improved detection accuracy compared to traditional methods.

Abstract