Diagnostics of Mixed Type Failures in the Aircraft Electromechanical Actuator Gear by Using Neural Networks

We proposed a method for designing the algorithms to determine the aircraft electromechanical actuators (EMA) technical condition by using the neural networks to simultaneously progress failures of various physical natures. We presented the results of the computational research on determining the EMA failures associated with changes in the dry friction and backlash in the gear.