Enhancing Fault Diagnosis in Cyber-Physical Systems : A Model-Based Approach with Bayesian Networks

The increasing complexity of cyber-physical systems has made it challenging to maintain their serviceability and diagnose faults. Model based diagnosis and Bayesian networks have been researched to diagnose faults in these systems. This study focuses on the use of a hybrid approach combining consistency-based diagnosis and Bayesian Networks to improve fault detection and diagnosis for complex systems. A relatively simple model of a cyber-physical system will be built and subjected to different health status node configurations to determine the best diagnosis performance. The proposed approach is expected to enhance fault diagnosis and maintain serviceability of cyber-physical systems.