Deep-Neural-Network-based anomaly detector for DC/DC power converter failure detection

Abstract

The Electrical Power Subsystem (EPS) of a spacecraft is paramount to its operation since it will guarantee that every piece of equipment is receiving its required power. Therefore, the reliability of the power subsystem is one of the cornerstones of the full spacecraft reliability. DC/DC converters are one of the main constituents of the power subsystems. A method able to estimate the degradation of a dc-dc converter would enhance the power system reliability. It would allow to detect dc-dc converters prone to failure and to take corrective actions to extend their remaining lifespan.