Industrial Automatic Control Systems and Controllers Annotation << Back Optimization Algorithm for Informative Features Extracting in Diagnostics of Aircraft Electromechanical Systems Veresnikov G.S., Skryabin A.V., Golev A.V. The use of machine learning methods in integration with methods for extracting informative features for diagnosing electromechanical systems (ES) is a promising area of scientifi c research related to solving the important scientifi c problem of ensuring the fl ight safety of modern aircraft. The paper proposes algorithms for extracting informative features that make it possible to build classifi cation models using machine learning methods to assess the technical condition of ES based on spectral analysis of stationary signals. A formalized description of the optimization models implemented in these algorithms is given. A scheme for performing optimization calculations to identify informative features is proposed. The results of computational studies are presented using the example of diagnosing the technical condition of the control surface electromechanical actuator of an aircraft. Keywords: diagnostics, electromechanical systems, aircraft, machine learning, informative features. DOI: 10.25791/asu.4.2024.1499 Pp. 17-24.