AMERICAN GNC CORP — National Aeronautics and Space Administration SBIR Phase I: H6
AMERICAN GNC CORP — SBIR Phase I award from National Aeronautics and Space Administration.
- Amount
- $124,999
- Agency
- National Aeronautics and Space Administration
- Program / Phase
- SBIR · Phase I
- Topic
- H6
- Solicitation
- SBIR_19_P1
- NAICS
- —
- Place of performance
- CA
- Period
- 2019-08-19 → 2020-02-18
Description
To support NASArsquo;s needs for health management technologies to increase safety and mission effectiveness for future space habitats, American GNC Corporation (AGNC) and Louisiana Tech University (LaTech) are proposing the ldquo;BRoad Advanced Intelligent Networked (BRAIN) Systemrdquo; consisting of: (i) an innovative Analysis Kernel with evolving cognition based on optimized deep neural networks and collaborative learning; (ii) recognition of new patterns and system trends by a novel Retrospective Change Point Detection (CPD) method for change analysis in temporally evolving systems; (iii) Human-System Integration Subsystem to support active learning to provide a friendly environment for human feedback; and (iv) Distributed Awareness Environment for consoles and optional mobile devices with voice activated commands and effective health information presentation (i.e. faults, data, features, fault cause-effect information, and maintenance actions).nbsp;The BRAIN system is tailored for processing NASA ISHM data. A cognitive approach is addressed, where deep learning schemes provide diagnostics capability and support to prognostics considering complex systems interrelations, big data, and uncovering unknown relationships among features. AGNCrsquo;s embedded Collaborative Learning Engine is infused and expanded to accommodate human feedback as a methodology for active learning and to process previously unknown system degradation. Two cases scenarios are approached to verify and validate the BRAINrsquo;s core technologies: (a) power system monitoring and interrelations with sensors in a fluid distribution system and (b) leakage detection in pipelines of a fluid distribution system.