Evaluation Testing of Learning-based Telemetry Monitoring and Anomaly Detection System in SDS-4 Operation
نویسندگان
چکیده
Health monitoring and anomaly detection techniques for artificial satellites are very significant, as it is very hard to repair those space systems on orbit. Authors have proposed the framework of learning-based anomaly detection that applies statistical machine learning and data mining techniques to the satellite telemetry data to automatically obtain normal behavior models which can be used for monitoring the health status of the system. In this study, we evaluated the learning-based anomaly detection method in the on-going operation of JAXA's satellite, SDS-4 (Small Demonstration Satellite 4), and obtained miscellaneous insights for putting this technology into practical use.
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