Edge Machine Learning Predictive Anomaly Detection for Autonomous Operations

The SSC Autonomous Systems Lab (ASL) will enhance autonomous systems capabilities for ground facilities and space systems that operate without internet connection. Microcontroller-based tinyML models will incorporate new fault detection and anomaly prediction capabilities into NPAS. Efforts are directed at demonstrating the ability of tinyML-enhanced NPAS to autonomously detect cavitation in cryogenic pumps.

Intelligent autonomous systems have the capacity to bolster systems by integrating machine learning (ML) with integrated system health management (ISHM), enabling decision making without the need for human intervention.

This is early/mid-stage (TRL 5) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

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