An Integrated Framework for Electronic Health Monitoring and Remaining Useful Life Estimation in Small Satellites

Abstract

The increasing reliance on nanosatellites and CubeSats for Earth observation, communication, and deep-space research has exposed the critical vulnerability of their onboard electronic systems to harsh space environments, including radiation, thermal cycling, and power fluctuations. Traditional telemetry monitoring relies on reactive, threshold-based methods that detect faults only after abnormal conditions manifest, often missing gradual degradation trends that lead to unexpected mission failures. To address this limitation, this paper proposes a lightweight, telemetry-driven predictive maintenance framework specifically designed for resource-constrained nanosatellite electronics. The proposed hybrid architecture combines onboard sensing, basic signal processing, and feature extraction with advanced ground-based predictive analytics. The system monitors key parameters, PCB temperature, bus voltage, current, battery status, and radiation exposure, to construct a unified Health Index (HI) that provides a comprehensive assessment of electronic health. Furthermore, the framework incorporates degradation trend analysis, Remaining Useful Life (RUL) estimation, and a digital twin environment to forecast system failures and enable proactive maintenance decisions. By shifting from reactive threshold monitoring to predictive intelligence, this framework aims to enhance the operational reliability, mission success rates, and lifespan of future CubeSat and nanosatellite missions.