1 - Embedded Condition Monitoring for Digital Logistics and Maintenance

The U.S. Navy relies on an expansive logistical system to ensure the operational readiness of our nation’s battle force ships, aviation equipment, facilities, and active duty personnel. The responsibility for procuring, distributing, and maintaining equipment and services depends on the reliable, efficient, and secure flow of information to determine the supply and repair needs for fragile or remote platforms and equipment. Luna proposes to develop a Health Awareness Framework that will provide accurate, secure, and resilient health assessments of critical machinery through embedded condition monitoring. This approach leverages a network of distributed sensor nodes that collect relevant operational, dynamic, and environmental data and use local signal processing and machine learning algorithms to identify key health features and failure modes to inform condition-based maintenance and prognostics (CBM+) practices. The Health Awareness Framework manages how data is reported and uses a fault tolerant design to ensure data integrity and sensor reliability, while able to react to communication dropouts, dynamic routing needs, and other potential issues that could impede the flow of data and results into legacy and emerging Navy information systems that oversee the logistical and maintenance needs to sustain operational availability of our ships, submarines, aircraft and facilities.