Instruments and Systems: Monitoring, Control, and Diagnostics Annotation << Back Fellow of the Federal State Institute of Management Problems S.A. SHILIN To improve the quality of decision making by the crew in this paper suggests using early diagnostic signs and prognostic data. Diagnostic signs must be installed for the input array on board unit assessment of the mechanical unit. In the framework of his working algorithm is proposed to put the apparatus of artificial neural networks. The result of the block is the conclusion of the early development of one or more defects. This information, along with the predictive block data is used for generating decision recommendations crew. Such an organization means onboard diagnostics allow in particular to carry out forecasting performance of the most important units of the time required for the successful completion of the flight. Keywords: mechanical defects, area diagnostic features, artificial neural network, growing pyramidal network Contacts: E-mail: stas@ipu.ru Pp. 47-51.