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Center Innovation Fund: SSC CIF

Embedded and Distributed Machine Learning for Prognostics Monitoring

Active Technology Project

Project Introduction

Embedded and Distributed Machine Learning for Prognostics Monitoring
Scheduled maintenance is inefficient and costly with no ability to take into account actual hardware degradation. The goal of this project is to develop a generic cost-effective embodiment that is relatively independent of the type of physical equipment being monitored by employing machine learning for prognostics monitoring. Prototype units will be developed with embedded novel machine learning algorithms for cryogenic equipment in the engine test complex as pilot demonstration systems. Energy harvesting technologies will also be integrated to further demonstrate low powered energy harvesting health monitoring capabilities. More »

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