Research/ SPACE AI & AUTONOMY

Telemetry Anomaly Detection System Using Machine Learning to Streamline Mission Operations

Michela Muñoz Fernández, Yisong Yue, Romann M. Weber

SMC-IT/SCC 2017/Sep 1, 2017/NASA Jet Propulsion Laboratory/ 24 citations

Space × AI

Technique

Autonomy, Task Planning & OperationsOpenAlex topic: Anomaly Detection Techniques and Applications · Learning-based MethodsOpenAlex keyword: machine learning · Guidance, Dynamics & ControlOpenAlex topic: Fault Detection and Control Systems

Missions

Curiosity (MSL)named in abstract, keywords

Indexed as

OpenAlexAnomaly Detection Techniques and Applications · Fault Detection and Control Systems · Spacecraft Design and Technology

DOI Semantic Scholar OpenAlex NASA NTRS

Spacecraft housekeeping telemetry is monitored at flight control centers by the operations engineers using tools that can perform limit checking or simple trend analysis. Recent developments in machine learning techniques for anomaly detection enables the implementation of more sophisticated systems that aim to augment current state-of-the-art mission tools to provide valuable decision support for the spacecraft operators, assisting in anomaly detection and potentially saving console time for the engineers. We will show some results of the implementation of an anomaly detection tool for the NASA Mars Science Laboratory mission.

Telemetry Anomaly Detection System Using Machine Learning to Streamline Mission Operations

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Telemetry Anomaly Detection System Using Machine Learning to Streamline Mission Operations

Related papers

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