Real-Time Signal Integrity Monitoring

The process for evaluating rocket engine test data is time-intensive and reactive. Operators must process the resulting data before sending it for manual review by analysts which can take several hours to days. Anomalies or performance deviations may go unnoticed until much later in the analysis cycle which impacts test efficiency. Develop an AI-driven configuration assistant that learns Expected Signal Behavior and detects Deviations in Real-Time and Integrates AI signal modeling and deviation detection into the NDAS’ TDMS processing pipeline. Potential of enabling broader aerospace and industrial test applications.

Dramatically reduce test turnaround time by providing real-time signal comparison against historical TDMS data using AI-assisted modeling. By leveraging prior test runs to create an expected signal envelope—and comparing current test data to that baseline—we can automatically flag anomalies as they occur and assess data quality prior to submitting for analysis.

This is a mature technology (TRL 7+) — the realistic path in is usually NASA's Technology Transfer Program: licensing an existing NASA patent, or a Space Act Agreement to use NASA facilities/expertise directly. NASA also runs a startup licensing program with no upfront fee for companies formed to commercialize a specific NASA technology.

None of these are guaranteed paths for this specific project — TechPort itself doesn't have an "apply" button. Reaching out to the contact(s) above with a specific question is usually the fastest way to find out what's actually open.