ORACLE - A PHM Test Validation Platform for Anomaly Detection in Crew Member Vital Sign Data

Wolfgang Fink, Shaun Brown, Mark A. Tarbell, Andrew Hess

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With NASA's push for prolonged stays aboard orbiting or surface-based space habitats (e.g., NASA Gateway/Artemis programs and successors) on the Moon and soon on Mars, there is a need for continuous monitoring of life support and mission critical systems deployed on these space habitats. Abiotic sensors will likely be used to detect anomalies aboard these space habitats, which we expect also to be embedded in a Prognostics and Health Management (PHM) framework. Recently, we introduced the concept of employing the crew member as a biosensor to be integrated into an overarching space habitat PHM system to increase the breadth of available data when monitoring environment health. Utilizing electrocardiogram (ECG) data as an example of a non-invasively obtained vital sign, we have devised a PHM test validation platform - the ORACLE - that auto-generates raw ECG data from previously extracted ECG motifs, ultimately representative of various conditions resulting from space habitat environment changes. The ORACLE emulates the occurrence of environmental changes and generates a log file to allow for training and subsequent deep learning-based anomaly detection frameworks, serving as a proof of concept for integration as a subsystem into a novel overarching PHM-based anomaly detection framework for monitoring space habitat health. The current version of ORACLE is equipped with an anomaly detection framework using multi-layer feedforward networks. This paper showcases the workings of the ORACLE and presents preliminary results for the deep learning-based anomaly detection framework. The ultimate goal is to use the measured 'biometric' changes in each crew member as a supplementary indicator to detect degradation in the space habitat environment and associated habitat subsystems. This novel indicator has the potential to enhance existing capabilities by providing for earlier detection than might otherwise be possible. The general idea is to use the crew health status as an integrated contributor to other PHM capabilities already implemented on associated space habitat subsystems.

Original languageEnglish (US)
Title of host publication2021 IEEE Aerospace Conference, AERO 2021
PublisherIEEE Computer Society
ISBN (Electronic)9781728174365
DOIs
StatePublished - Mar 6 2021
Event2021 IEEE Aerospace Conference, AERO 2021 - Big Sky, United States
Duration: Mar 6 2021Mar 13 2021

Publication series

NameIEEE Aerospace Conference Proceedings
Volume2021-March
ISSN (Print)1095-323X

Conference

Conference2021 IEEE Aerospace Conference, AERO 2021
Country/TerritoryUnited States
CityBig Sky
Period3/6/213/13/21

ASJC Scopus subject areas

  • Aerospace Engineering
  • Space and Planetary Science

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