A Data-Driven Approach to Cubesat Health Monitoring [thesis]

Serbinder Singh
Spacecraft health monitoring is essential to ensure that a spacecraft is operating properly and has no anomalies that could jeopardize its mission. Many current methods of monitoring system health are difficult to use as the complexity of spacecraft increase, and are in many cases impractical on CubeSat's which have strict size and resource limitations. To overcome these problems, new data-driven techniques such as Inductive Monitoring System (IMS), use data mining and machine learning on
more » ... e learning on archived system telemetry to create models that characterize nominal system behavior. These characterizations can then be autonomously compa red against real-time telemetry on-board the spacecraft to determine if the spacecraft is operating nomin ally. This paper presents an adaption of IMS to create a spacecraft health monitoring system for CubeSat missions developed by the PolySat lab. This system is integrated into PolySat's flight software and provides real time health monitoring of the spacecraft during its mission. Any anomalies detected are reported and further analysis can be done to determine the cause. The system was successful in the detection and identification of known anomalies in archived flight telemetry from the IPEX mission. In addition, real-time monitoring performed on the satellite yielded great results that give us confidence in the use of this system in all future missions.
doi:10.15368/theses.2017.100 fatcat:sbaoc72vxjf3flkzewxz5yphzy