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Development of False Alarm Mitigation Techniques

Award Information

Agency:
Department of Defense
Branch:
Navy
Award ID:
75103
Program Year/Program:
2005 / SBIR
Agency Tracking Number:
N051-028-0497
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
INTELLIGENT AUTOMATION CORP.
13029 Danielson Street Suite 200 Poway, CA 92064-8811
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2005
Title: Development of False Alarm Mitigation Techniques
Agency / Branch: DOD / NAVY
Contract: N68335-05-C-0258
Award Amount: $79,999.00
 

Abstract:

An essential premise motivating the Joint Strike Fighter Prognostics and Health Management (JSF-PHM) approach is the capability of correctly detecting faults in components or subsystems. Whether a fault is declared according to time series recordings by monitored on-board sensors, or by sophisticated reasoning algorithms that recognize slow changes in behavior as a component degrades over time, fault detection must be performed correctly. Otherwise, failed components may not be replaced as necessary, or one may be unnecessarily serviced due to a false alarm. Both types error interfere with the attainment of AL objectives of minimizing aircraft support and logistics costs. JSF-PHM demands novel algorithmic methods to eliminate false alarms. This is a challenging task, since classification algorithms intended to detect anomalies (unrecognized faults) learn data probability distributions in known fault condition space. Extrapolation outside the training data is problematic; however this is exactly the region where anomalies are expected to occur. Faced with an anomalous condition, proper discrimination between "fault" and "no-fault" will determine the overall false alarm rate of the PHM system. This proposal describes a novel means to achieve a minimal false alarm rate at a given, fixed level of statistical confidence.

Principal Investigator:

Joel Bock
Principal Investigator
8586794140
joel.bock@iac-online.com

Business Contact:

Nicholas Brunski
Contracts Manager
8586794140
nick.brunski@iac-online.com
Small Business Information at Submission:

INTELLIGENT AUTOMATION CORP.
13029 Danielson Street, Suite 200 Poway, CA 92064

EIN/Tax ID: 330876270
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No