Automation of Health Management, Troubleshooting and Recovery in Lunar Outpost

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NNX10CC37P
Agency Tracking Number: 095761
Amount: $99,868.00
Phase: Phase I
Program: SBIR
Awards Year: 2010
Solitcitation Year: 2009
Solitcitation Topic Code: X1.01
Solitcitation Number: N/A
Small Business Information
Qualtech Systems, Inc.
100 Great Meadow Road, Suite 603, Wethersfield, CT, 06109-2355
Duns: 808837496
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Sudipto Ghoshal
 Principal Investigator
 (860) 761-9341
 sudipto@teamqsi.com
Business Contact
 Sudipto Ghoshal
Title: VP, Engineering
Phone: (860) 761-9341
Email: sudipto@teamqsi.com
Research Institution
N/A
Abstract
NASA's Lunar and other future extraterrestrial outposts will be built for long duration missions that are likely to experience significant number of faults and degradations over its lifetime. Additionally, these systems will have a highly reconfigurable architecture and perform multimodal operation. Being a resource constrained environment, health management, troubleshooting, maintenance, and repair of the Lunar outpost poses formidable challenge. To address this challenge Qualtech Systems, Inc. proposes to automate a major part of the HM and recovery decision support systems through a TEAMS-based approach. The approach will provide the facility to develop on-the-fly reconfigurable diagnostic models that can be used to automatically update a TEAMS model upon configuration changes. Residual functional capability estimation techniques and automatic updating of diagnostic models based on current condition of components will be developed through this effort. Dynamic multiple fault diagnosis techniques will be used for enhancing the diagnostic accuracy obtained from TEAMS-based diagnosis. Such accuracy enhancement will greatly reduce the amount of human intervention required in troubleshooting of spurious faults, and faults that are isolated with a large ambiguity group. On the overall, the proposed effort will provide a solution for automating the HM related activities in highly reconfigurable systems with resource constraints.

* information listed above is at the time of submission.

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