Failure Precursors and Anomaly Detection in Complex Electrical Systems Using Symbolic Dynamics

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-05-C-0096
Agency Tracking Number: N043-258-0631
Amount: $80,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2005
Solicitation Year: 2004
Solicitation Topic Code: N04-258
Solicitation Number: 2004.3
Small Business Information
INTELLIGENT AUTOMATION, INC.
15400 Calhoun Drive, Suite 400, Rockville, MD, 20855
DUNS: 161911532
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 Chiman Kwan
 Vice President of R & D
 (301) 294-5238
 ckwan@i-a-i.com
Business Contact
 Mark James
Title: Contract Manager
Phone: (301) 294-5221
Email: mjames@i-a-i.com
Research Institution
N/A
Abstract
Failures in a plant's electrical components are a major source of performance degradation and plant unavailability. In order to detect and monitor failure precursors and anomalies early in electrical systems, we propose to develop signal processing capabilities that can detect and map patterns in already existing, available signals to an anomaly measure. Toward this end Professor Asok Ray at Penn State University has pioneered an elaborate mathematical theory of "language measure" based on real analysis, finite state automaton, symbolic dynamics and information theory. Application of this theory for anomaly detection results in a robust statistical pattern recognition technique. This technique is superior to conventional pattern recognition techniques such as neural networks and principal component analysis for anomaly detection because it exploits a common physical fact underling most anomalies which conventional techniques do not. This superiority has recently been demonstrated on electrical circuits, lasers and in mechanical components. The objectives of the research proposed by Intelligent Automation Incorporated (IAI) and its subcontractor are: (i) to develop real-time anomaly sensing and monitoring systems for early detection of faults in avionic electrical systems; and (ii) to experimentally validate the proposed concept on an active nonlinear electrical circuit.

* information listed above is at the time of submission.

Agency Micro-sites

SBA logo
Department of Agriculture logo
Department of Commerce logo
Department of Defense logo
Department of Education logo
Department of Energy logo
Department of Health and Human Services logo
Department of Homeland Security logo
Department of Transportation logo
Environmental Protection Agency logo
National Aeronautics and Space Administration logo
National Science Foundation logo
US Flag An Official Website of the United States Government