A Neural Network-based System for Automated Detection of Wire Insulation Chafing from TDR/FDR Data

Award Information
Agency: Department of Transportation
Branch: N/A
Contract: DTRS57-02-C-10016
Agency Tracking Number: DTRS57-02-C-10016
Amount: $99,976.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Timeline
Solicitation Year: N/A
Award Year: 2001
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
6022 Constitution Avenue NE, Albuquerque, NM, 87110
DUNS: N/A
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 () -
Business Contact
Phone: () -
Research Institution
N/A
Abstract
This proposal is to develop an automated system for identification and characterization of chafing in the aircraft wiring. Chafing degrades wiring integrity and can lead to shorts and/or damaged data pathways. Shorts have been associated with deadly in-flight fires. Damaged data pathways have caused engine shutdowns, loss of control, and other safety hazards. Currently recognizing and measuring chafing requires an expensive and time-consuming process of visual inspection. We propose development of an automated system for identification and characterization of chafing from Time Domain Reflectometry (TDR) or Frequency Domain Reflectometry (FDR) data. At the end of Phase I, we will demonstrate the feasibility of using neural network technology to enable automated chafing identification from reflectometry data. We will also design and prototype an automated chafing identification system suitable for use in portable inspection equipment for aircraft wiring.

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

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