Digital twin of the tripping coils for health monitoring and diagnostics of medium voltage circuit breakers

Tripping coils are crucial components of circuit breakers, responsible for initiating both closing and opening operations. Their reliability is vital, particularly in case of faults or abnormal situations, as they ensure the circuit breaker can interrupt current. This study aims to develop a digital twin to model the electromagnetic and mechanical behavior within the tripping coil using ordinary differential equations (ODEs). Health diagnostics is then performed by applying optimization procedures to identify and quantify drifted model parameters. Based on these results, case-specific warnings and recommendations can be provided. The digital twin is designed to be integrated into an AI-based assistance system to facilitate predictive maintenance for network operators.