TY - JOUR AU - Potapov, Valentin PY - 2016/12/21 Y2 - 2024/03/29 TI - CLASSIFICATION OF NEURAL NETWORK FOR TECHNICAL CONDITION OF TURBOFAN ENGINES BASED ON HYBRID ALGORITHM JF - Proceedings of National Aviation University JA - Proceedings of National Aviation University VL - 69 IS - 4 SE - MODERN AVIATION AND SPACE TEHNOLOGY DO - 10.18372/2306-1472.69.11057 UR - https://jrnl.nau.edu.ua/index.php/visnik/article/view/11057 SP - 64-68 AB - <strong><em>Purpose:</em></strong><em> This work presents a method of diagnosing the technical condition of turbofan engines using hybrid neural network algorithm based on software developed for the analysis of data obtained in the aircraft life.</em> <strong><em>Methods:</em></strong><em> allows the engine diagnostics with deep recognition to the structural assembly in the presence of single structural damage components of the engine running and the multifaceted damage. <strong>Results:</strong> of the optimization of neural network structure to solve the problems of evaluating technical state of the bypass</em><strong> </strong><em>turbofan engine, when used with genetic algorithms.</em> ER -