Fault-to-Failure Progression Modeling for Propulsion and Drive Train Clutch Systems

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-03-C-0190
Agency Tracking Number: N031-1304
Amount: $69,965.00
Phase: Phase I
Program: SBIR
Awards Year: 2003
Solitcitation Year: N/A
Solitcitation Topic Code: N/A
Solitcitation Number: N/A
Small Business Information
IMPACT TECHNOLOGIES, LLC
125 Tech Park Drive, Rochester, NY, 14623
Duns: 073955507
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Carl Byington
 Director, Research and De
 (814) 861-6273
 carl.byington@impact-tek.com
Business Contact
 Mark Redding
Title: President
Phone: (585) 424-1990
Email: mark.redding@impact-tek.com
Research Institution
N/A
Abstract
Impact Technologies, in collaboration with Rolls Royce, proposes to develop and demonstrate a prognostic modeling paradigm for use with drive train components. Drive train and clutch systems on modern weapons platforms are highly dynamic and have thepotential for high load densities due to compact packaging. Between the many different elements of the drive system there is an extensive amount of functional interaction and dependency, which complicates the tracking of faults as they progress to thepoint of compromising function (failure). To address this coupling dependency, Impact will apply system models, suitable wear and fatigue failure mode progression (prognostic) algorithms, and advanced knowledge fusion in a probabilistic framework and applyit to drive line components such as: clutches, gears, bearings and shafts. Initial focus will be on a Joint Strike Fighter clutch mechanism. A verification plan with consideration to the Rolls Royce drive train development program will also be evaluatedfor this prognostic approach. The ability to assess drive train clutch health and produce more accurate time-to-failure predictions through sensor feature observation, performance and damage models, uncertainty estimation, and confidence interval faultevolution predictions in near real-time will result in operational benefits through a reduced risk of safety-related system failures and increased system readiness. In addition, maintenance benefits will occur through a decrease in costly preventativemaintenance/overhauls and transition to prognostic health management and autonomic logistics strategies. The failure progression modeling techniques could be implemented in a wide range of military applications including the Joint Strike Fighter, AdvancedAmphibious Assault Vehicle, Landing Craft Air Cushion, and many ground (tank and truck) vehicles. The developed technologies could also be readily adapted to commercial land and water vehicle drive systems, industrial actuation systems, andmanufacturing/processing applications.

* information listed above is at the time of submission.

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