[4F3-OS-30c] OS-30

[4F3-OS-30c-05] Investigation of onboard anomaly identification methods for artificial satellites

〇Shun Katsube¹, Hironori Sahara¹ (1. Tokyo Metropolitan University)

Keywords:Anomaly detection, Onboard, Prognostics and health management, Satellite

Artificial satellites are equipped with Fault Detection, Isolation and Recovery (FDIR) systems to ensure operational stability, and current FDIR systems are constructed using a primitive method that defines a threshold value for each telemetry data. However, the conventional FDIR systems have operational limitations because it requires a lot of expert knowledge and human resources to design appropriate thresholds for hundreds or thousands of telemetry data. In this study, we aim to construct a data-driven FDIR system and investigate a new data-driven anomaly identification method. The proposed method not only detects anomalies, but also identifies the type and location of the detected anomaly with a computational cost that can be implemented onboard. We also report the results of applying the proposed method to a dummy abnormal voltage data and discuss its anomaly detection and identification capabilities.