The Monitoring of the Spacecraft Equipment Thermal Modes

P. 319–323.

Istratov A. Yu., Khomenko I. I., Pogodin A. V.

This paper introduces the approach to the temperature parameters forecasting to avoid overheating of the spacecraft equipment at the end of the data transmission session during which information from temperature detectors are unavailable. It is essential to prevent situations in which spacecraft’s details will experience excessive overheating because it leads to the failure of major components. To determine the unknown temperature values of the spacecraft components based on current temperature mode and spaceship orientation parameters’ values at the indicated times algorithms for historiсal data processing are proposed. Preprocessing techniques were applied to the raw data accumulated during the operation period. The software for temperature parameters forecasting based on current orientation and temperature of the spacecraft’s components is provided. The conducted experiments proved the ability to reveal anomaly thermal situations and it was showed that the result error was small enough to accurately predict the possibility of overheating to prevent the spacecraft equipment failure.

Keywords: neural networks, spacecraft, data analysis, machine learning, temperature characteristics, monitoring of temperature pattern, Radial Basis Functions, Temperature Detectors

In book

2016 Third International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC)

M.: IEEE, 2016.