Embedded Spacecraft Fault Detection

Abstract

Small satellites increasingly produce more housekeeping telemetry than can be continuously downlinked or inspected, delaying operator awareness of emerging spacecraft-health issues. This thesis develops an explainable on-board thermal anomaly-alerting pipeline for downlink-constrained small-spacecraft missions, using Delfi Twin as a case study. Rather than proposing a stand-alone anomaly-detection algorithm, it defines a deployment pathway linking telemetry scope, anomaly semantics, synthetic event-level evaluation, residual-to-alert decision logic, compact alert packets, and STM32L4-class embedded verification. A lightweight expected-temperature predictor is combined with residual scoring, cumulative evidence, persistence, hysteresis, transient-spike suppression, and explicit gap termination to form bounded detector events. A labelled synthetic benchmark enables quantitative evaluation, while FUNcube-1 telemetry provides qualitative stress evidence on real on-orbit data. Under matched-predictor conditions, all alert-worthy synthetic events were recovered, and STM32L4 replay demonstrated ample timing and memory margins. Flight performance and autonomous operational trust remain future validation tasks.