Electromechanical actuators (EMAs) have shown a high efficiency in flight surface control with the development of more electric aircraft. In order to identify the abnormalities and potential failures of EMA, a methodology for fault diagnosis is developed. A simulating model of EMA is first built to perform different working states. Based on the modeling of EMA, the corresponding faults are then simulated to re-generate the fault data. Afterwards, a gated recurrent unit (GRU) and co-attention-based fault diagnosis approach is proposed to classify the working states of EMA. Experiments are conducted and a satisfying classification accuracy on simulated data is obtained. Furthermore, fault diagnosis on an actual working system is performed. The experimental results demonstrate that the proposed method has a high efficiency.
