Application of a Neural Network for the Analysis of the “Soyuz” Launch Vehicle Boosters’ Separation.

Abstract

The paper discusses application of artificial intelligence (neural networks) technologies for automated analysis of dynamic processes of the “Soyuz” launch vehicle’s onboard systems. Cyclogram of strap-on boosters separa-tion as applied to this task, and telemetry measurement used to monitor this process are described. The general information about the construction of the used types of neural networks and about their learning using a back-propagation method is presented; the neural network configuration for solving the mentioned task, telemetry presentation format suitable for sup-plying power for the neural network, and features of the neural network learning are proposed. The approbation of the trained neural network for the analysis of launches of the “Soyuz-FG” and “Soyuz-2.1a” launch vehi-cles using telemetry in real-time and delayed modes was carried out.