Fault management for a Three Mass Torsion Oscillator

A model-based fault management system for a Three Mass Torsion Oscillator is described. Fault management includes fault detection, fault diagnosis and fault compensation. A process model of system dynamics is derived. Friction effects are modelled by a neuro-fuzzy Local Linear Model Tree (LOLIMOT) approach. Parameter estimation is obtained with two simple experiments. A friction estimation stage is used to support fault diagnosis and potential control applications. Parity equations are used to detect and diagnose speed sensor failures. In case of sensor failures, the fault management system initiates reconfiguration operations. The failure of one sensor is compensated by substituting the sensor signal with the output of a process model fed by other, intact sensors. The methods presented are evaluated using experimental measurements of a test rig.