Actuator fault diagnosis and severity identification of turbofan engines for steady-state and dynamic conditions

Abstract

Actuator faults can be critical in turbofan engines as they can lead to stall, surge, loss of thrust and failure of speed control. Thus, fault diagnosis of gas turbine actuators has attracted considerable attention, from both academia and industry. However, the extensive literature that exists on this topic does not address identifying the severity of actuator faults and focuses mainly on actuator fault detection and isolation. In addition, previous studies of actuator fault identification have not dealt with multiple concurrent faults in real time, especially when these are accompanied by sudden failures under dynamic conditions. This study develops component-level models for fault identification in four typical actuators used in high-bypass ratio turbofan engines under both dynamic and steady-state conditions and these are then integrated with the engine performance model developed by the authors. The research results reported here present a novel method of quantifying actuator faults using dynamic effect compensation. The maximum error for each actuator is less than 0.06% and 0.07%, with average computational time of less than 0.0058 s and 0.0086 s for steady-state and transient cases, respectively. These results confirm that the proposed method can accurately and efficiently identify concurrent actuator fault for an engine operating under either transient or steady-state conditions, even in the case of a sudden malfunction. The research results demonstrate the potential benefit to emergency response capabilities by introducing this method of monitoring the health of aero engines.