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A Thin Film Transistor Based Ultrasonic Sensor for Aircraft Integrity Monitoring

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NND05AA52C
Agency Tracking Number: 040056
Amount: $100,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: T2.02
Solicitation Number: N/A
Timeline
Solicitation Year: 2004
Award Year: 2005
Award Start Date (Proposal Award Date): 2005-01-27
Award End Date (Contract End Date): 2006-01-23
Small Business Information
15400 Calhoun Drive, Suite 400
Rockville, MD 20855-2785
United States
DUNS: 161911532
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Chiman Kwan
 Principal Investigator
 () -
 ckwan@i-a-i.com
Business Contact
 Mark James
Title: Contracts Manager
Phone: (301) 294-5221
Email: mjames@i-a-i.com
Research Institution
 Pennsylvania State University
 Robert Killoren
 
110 Technology Center
University Park, PA 16802
United States

 (814) 865-1372
 Domestic Nonprofit Research Organization
Abstract

Intelligent Automation, Incorporated (IAI) and its subcontractor, Penn State U., propose a novel system to detect damage in aircraft structures. The system combines novel TFT based thin film actuators and sensors for signal acquisition and a robust software for fault prognosis and diagnosis. The actuator/sensor is known as PVDF-IDT (Polyvinylidine Fluoride Interdigital Transducer) that is integrated into a TFT switching circuit. It is low cost, compact, flexible, and has great potential for wireless interrogation. PVDF-IDT sensor has been proven to be useful for sensing cracks in rivet holes as well as other structural defects such as corrosion, delamination, and fatigue cracking. The second element of the system is an automatic fault prognosis tool, which consists of Principal Component Analysis (PCA), Learning Vector Quantization (LVQ), and Hidden Markov Model (HMM). PCA is a popular neural network tool for extracting useful features. LVQ is used to generate the code sequence. HMM has been proven to be extremely useful in several applications, however, HMM is used here to perform both fault prognosis and diagnosis. Our proposed system can perform continuous monitoring of aircraft structures in both ground and in-flight situations, and the sensors can be easily embedded into the structure.

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

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