The paper considers the electromechanical actuator technical condition determination methods using the frictional energy losses and position diagnostic features. The substantiation of the selected features is given by the example of the tested prototype of control surface electromechanical actuator with a roller screw gear. The mechanical faults influence on the position accuracy is shown. Electromechanical actuator technical state estimation algorithms that use the machine learning methods are proposed and tested on simulation data.