FAST PHM™ - An Integrated Process and False Alarm Mitigation Design Tool for PHM

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$749,941.00
Award Year:
2006
Program:
SBIR
Phase:
Phase II
Contract:
N68335-07-C-0097
Agency Tracking Number:
N051-028-0286
Solicitation Year:
2005
Solicitation Topic Code:
N05-028
Solicitation Number:
2005.1
Small Business Information
IMPACT TECHNOLOGIES, LLC
200 Canal View Blvd, Ste 300, Rochester, NY, 14623
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
073955507
Principal Investigator:
Carl S Byington
Director, Research and De
(814) 861-6273
carl.byington@impact-tek.com
Business Contact:
Mark Redding
President
(585) 424-1990
mark.redding@impact-tek.com
Research Institution:
n/a
Abstract
Impact Technologies proposes to develop an open-interface software module encapsulating the algorithms and statistical analysis package used in verification software test environment. Developments include system-engineering analysis to identify the additional technical and procedural sources of false alarms, models and analysis techniques to be used for mitigation in addition to analysis of rate and time-based false alarm performance metrics. The result will be achieved through an assessment of the best technical approaches for PHM design using limited sources of fault data and models. Impact’s False Alarm Statistics Toolbox (FAST™) enables the user to access the integrated toolset through a graphical user interface to determine the optimal strategy for false alarm mitigation on a fleet-wide basis. The toolset builds upon PHM design guidelines developed for false alarm mitigation coupled with vibration and non-vibration based datasets. Standardized analysis metrics are implemented to characterize the performance of a variety of features derived from Impact’s PHM modules including ImpactEnergy™ bearing fault detection, GearMod™ gear fault detection and user-defined feature extraction routines. Impact will demonstrate the FAST™ product across a variety of datasets while implementing a suite of algorithms including: sensor validation, mode detection, feature extraction, feature fusion, fault detection, fault classification, threshold selection and reasoning.

* information listed above is at the time of submission.

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