SBIR/STTR Research Award

Real-Time Prognostic Health Management for Fault Tolerant Airborne Laser Systems

Award identifier 7c87d2644ca1b7fe02018cc96df4cb012827949755997b253156db63982032f3Awarding agency Department of Defense · Missile Defense Agency

Award amount

$69,995

Program and phase

STTR · Phase I

Award year

2003

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Missile Defense Agency
Recipient company
ACTA, LLC
Proposal award date
Not reported
Contract end date
Not reported
UEI
DFJ9T2AMP233
Solicitation number
Not reported
Topic code
Not reported

Research abstract

The proposed project will demonstrate the feasibility of developing a data driven prognostic fault tolerant smart weapon system concept for the Airborne Laser. A real-time prognostic health management (PHM) system will be developed to track the likelihoodof future system or subsystem failures and initiate or indicate appropriate actions to maintain or optimize system performance. A library of predictive algorithms will be employed to take large multi-dimensional data sets as input and provide advancedwarning of specific failure, fault and error events to help manage the health of the ABL in an automated way. A principal components approach is proposed to analyze and quantify the uncertainty of target fault signatures. An on-board Consequence Engineis proposed to achieve a real-time fault tolerant, self-healing, smart weapon system while maintaining high mission success probability. A preliminary prototype demonstration will be carried out on a system or subsystem identified by ACTA and Team ABL.The ABL weapon system offers many challenges in the predictive maintenance of its combat effectiveness, range and crew safety, airworthiness, and operational cost. A data driven real-time prognostic health management system can help meet these challengesby providing continuous health monitoring for fault tolerant systems using prognostic data. A prognostic system that enables self-awareness, self-healing, and self-health management is particularly important for mobile weapon systems such as the ABL. Aprognostic system provides vital information that can assist in refining the existing system or procuring future systems. Other potential applications involve predictive health management of critical assets such as a Space Based Laser (SBL) and GroundBased Laser (GBL), aircraft components, machinery, and industrial processes. The broad commercial potential of the predictive engines developed from this project will expand ACTA's capabilities in providing risk analysis and management services tocommercial and government clients. In addition, the technology acquired under this project will help ACTA to develop a Consequence Engine for the structural health monitoring system being developed for NASA.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

47 SBIR/STTR records share this UEI (1987–2017). Reported award amounts total $14,477,317. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, National Science Foundation

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.