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Life Usage and Health Assessment of Drivetrain Splines in Support of Condition Based Maintenance (CBM)

Award Information
Agency: Department of Defense
Branch: N/A
Contract: N68335-11-C-0205
Agency Tracking Number: N093-170-0206
Amount: $749,969.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: N093-170
Solicitation Number: 2009.3
Timeline
Solicitation Year: 2009
Award Year: 2011
Award Start Date (Proposal Award Date): 2011-03-16
Award End Date (Contract End Date): N/A
Small Business Information
200 Canal View Blvd
Rochester, NY -
United States
DUNS: 073955507
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Avinash Sarlashkar
 Director, Technology
 (585) 424-1990
 avinash.sarlashkar@impact-tek.com
Business Contact
 Mark Redding
Title: President
Phone: (585) 424-1990
Email: mark.redding@impact-tek.com
Research Institution
 Stub
Abstract

Given the drivetrain issues on the tail rotor splined shaft for the Seahawk, there is a need for robust tools that will provide better design guidance, provide current health status as well as provide prognostic capabilities for gearbox splines. To meet this need, Impact Technologies, LLC proposes to develop and demonstrate a spline health assessment and prognosis system that will utilize physics-based spline lifing models in conjunction with vibration data to produce actionable life usage and health assessment feedback. We intend to create a comprehensive technology suite that will accurately and quickly assess the impact of past and future vehicle usage on spline health status and therefore, on overall gearbox and vehicle reliability and mission readiness. The approach will consist of identifying and quantifying spline faults including fretting-fatigue-induced crack initiation and subsequent crack propagation. Accurately characterizing the current health will allow improved estimates for remaining useable life. The development of spline health models will require modeling, material characterization, and testing as well as the use of sensor data and tuned vibration-based feature algorithms.

* Information listed above is at the time of submission. *

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