Automated Contingency and Life Management for Integrated Propulsion and Power Systems

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-05-C-2607
Agency Tracking Number: F041-189-1830
Amount: $746,324.00
Phase: Phase II
Program: SBIR
Awards Year: 2005
Solicitation Year: 2004
Solicitation Topic Code: AF04-189
Solicitation Number: 2004.1
Small Business Information
IMPACT TECHNOLOGIES, LLC
200 Canal View Boulevard, Rochester, NY, 14623
DUNS: 073955507
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Carl S Byington
 Director, Research & Deve
 (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 and Honeywell Engines, Systems, and Services propose the development and validation of an Automated Contingency and Life Management (ACLM) system for integrated propulsion and power systems. The ACLM will combine advanced prognostic health monitoring (PHM) capabilities with engine and power system control, thus enabling utilization of performance and health information for optimal mission planning and execution. The ACLM will comprise of two functional modules: Prognostic Health Management (PHM) and Adaptive Intelligent Control (AIC). During Phase I, Impact developed an architecture, along with prototype PHM and AIC algorithms, and demonstrated them on a generic jet engine simulation model. The on-line generic PHM algorithms utilize a combination of sensor data, signal processing, data/knowledge fusion, physical/empirical models and an integrated probabilistic reasoner to predict degraded performance or health conditions. During Phase II, Impact and Honeywell will adapt the PHM algorithms for application to engine, generator, lubrication system and gearbox health analysis for Honeywell’s F124 engine. The PHM algorithms will include model-based parameter estimation, vibration monitoring, fault pattern recognition, and evolutionary prognostic techniques. The PHM system will use multiple algorithms on each subsystem and fuse their outcomes to improve the confidence of fault and health prognosis of each subsystem and its components. The hierarchical AIC module will use PHM information to perform a capability assessment of its respective system and perform operation re-planning and optimization, if necessary. Impact will demonstrate the ACLM system, along with its PHM algorithms, on test stands for individual systems and will validate the results by comparing them with engine test cell data.

* information listed above is at the time of submission.

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