Model-based fault diagnosis in rotor systems with self-sensing piezoelectric actuators

Machines which are developed today are highly automated due to increased use of mechatronic systems. Fault detection and isolation are important features to ensure their reliable operation. This research work aims to achieve an integrated control and fault detection functionality with minimum number of components.

Piezomaterials can be used both as sensors and actuators due to their inherent coupling between electrical and mechanical properties. In this thesis, piezoelectric actuators which are being researched for active vibration control on flexible rotors, are also used as sensors. These self-sensing actuators reconstruct their mechanical deflection from the measured voltage and current signals. The systems under investigation are a numerical aircraft engine model and its scaled representation in a rotor test bench. Since the actuators are mounted in rotor bearings, their displacement represent the bearing deflection directly.

In this research work, the virtual sensor signals are utilised for model-based fault diagnosis in rotor systems, with focus on unbalances in rotors. Unbalance magnitude and phase were estimated in frequency domain using a parameter estimation method by least squares optimisation. The robustness of the estimates against signal outliers is improved by method of M-estimators. Identifying the fault location is also explored using the hypothesis of localization of faults.

In simulation, models of both systems (aircraft engine and test bench) were used to detect unbalance faults. In the former system, the influence of actuator placements in fault detection ability is examined. The fault detection method is also validated at the real test bench, as a first step. The unbalance detected using the measured virtual sensor signals is compared against results using available physical sensors. They are found to be in good agreement which proves sensing capability of the actuators. This sensor-minimal approach could be favoured in systems with space constraints.

As a further step, unbalances are detected with self-sensing piezoelectric actuators in closed loop with an adaptive algorithm for vibration minimisation. This combined control effort and fault detection as a strategy, is suitable to augment level of automation in a machine.