Semiautonomous Anomaly Monitoring and Early Detection (SAMY) System

NASA Ames Research Center (ARC)s innovative autonomous operations technologies (AOT) for ground and launch systems require minimized or even eliminated human iteration/intervention, and presence due to hazardous operational environments. Towards this goal, American GNC Corporation (AGNC) and The University of Texas at Arlington (UTA) are proposing the Semiautonomous Anomaly Monitoring and Early Detection (SAMY) System to advance NASAs operations and maintenance (OM) infrastructure while increasing ground system availability to support mission operations. The SAMY system is to provide innovative Prognostics and Health Management (PHM) technology for planetary or lunar surface-based infrastructure that are related to the preparation of launch vehicles and payloads for flight. SAMY can also improve NASAs Stennis Space Center (SSC) test stand infrastructure by taking into account earth applications. The system builds upon: (i) automated anomaly detection, analysis, and characterization (ADAC) to identify incipient fault conditions and benign new operational conditions; (ii) generalized prognostic methodology based on optimized Multilayer Perceptron (MLP) discriminant; and (iii) suite of cutting edge algorithms operating collaboratively, including semiautomated incremental learning, selected deep learning paradigms, and inference methods for both Fault Detection and Identification (FDI) and guidance in maintenance operations. Phase II design constraints include: (a) developing a sound framework that can handle with concept drift and structured data (e.g., multi-source, distributed, and heterogenous); (b) automated new knowledge assimilation once that change is detected and found a new condition; (c) developing a generalized prognostics scheme to provide Remaining Useful Life estimations; (d) blending strengths of advanced machine learning paradigms and achieving collaborative operation while for Prognostics and Health Management system; and (e) thorough VV NASA Ames Research Center (ARC)'s innovative autonomous operations technologies (AOT) for ground and launch systems require minimized or even eliminated human iteration/intervention, and presence due to hazardous operational environments. The SAMY system is to provide innovative Prognostics and Health Management (PHM) technology for planetary or lunar surface-based infrastructure that are related to the preparation of launch vehicles and payloads for flight. SAMY can also improve NASA's earth facilities (e.g., Stennis Space Center (SSC) test stand infrastructure). The system builds upon: (i) automated anomaly detection, analysis, and characterization (ADAC) to identify incipient fault conditions and benign new operational conditions; (ii) generalized prognostic methodology based on optimized Multilayer Perceptron (MLP) discriminant; and (iii) suite of cutting edge algorithms operating collaboratively, including semiautomated incremental learning, selected deep learning paradigms, and inference methods for both Fault Detection and Identification (FDI) and maintenance guidance. The overall goal of Phase II is to provide a complete prototype of the SAMY with demonstrations of its utility as cutting-edge PHM software toolbox. The following technical objectives will enable achieving this goal: (1) Providing automated ADAC for enhancing NASA AOT; (2) Optimizing Collaborative Cognitive System for Advanced FDI and Prognostics; (3) Building a Health Monitoring Foundation for the Generation of Suitable AOT for NASA Ground and Launch Systems; (4) Conducting Thorough Verification and Validation (V&V) and Demonstration to Achieve High TRL and Towards Integration.   The Phase II Tasks include: (1) Multilayer Perceptron (MLP) Discriminant Enhancement for Incipient Fault Awareness; (2) Semi-Autonomous Evolving Cognitive Kernel for Diagnostics and Incipient Fault Awareness; (3) Remaining Useful Life Estimation; (4) Data Fusion and High-Level Analysis of the Discriminant, Enhanced eCLE, and Prognostics Inference Results; (5) Framework Optimization for execution time, distributed processing, and computational complexity, and systems with SWAP constraints; (6) Maintenance Support and Enterprise Infrastructure for Ubiquitous Health Data to Users;(7) Conducting V&V of Core Technologies   Deliverables: (1) progress reports; (2) final report; (3) software projects and source code files necessary for deploying the SAMY System; (4) user manual; and (5) system demonstration.

The primary target is NASA ground and launch systems for planetary and lunar surface infrastructure. The applications are numerous since SAMY is a PHM software product that supports AOT and O&M infrastructure, being examples: Advanced Ground Systems Maintenance (AGSM) and Integrated Health Management (IHM) Architecture at the Kennedy Space Center; NASA Ames autonomous systems, space habitats, and spacecrafts; and NASA Stennis Space Center (SSC) space launch systems (SLS) such as vacuum jacketed pipelines, and liquid nitrogen high-pressure pump. SAMY focus to anomaly detection, prognostics, & FDI based on cognitive systems ensemble, puts it apart from current commercial products. Potential markets include Condition Based Maintenance, Smart Sensors, Internet of Things, & Autonomous Systems. Specific applications are avionic systems, manufacturing, structural health monitoring, fluid distribution systems, chemical processing plants.

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