SBIR Phase I: Automated Structural Health Monitoring Sensor

Award Information
Agency:
National Science Foundation
Branch
n/a
Amount:
$99,984.00
Award Year:
2006
Program:
SBIR
Phase:
Phase I
Contract:
0539234
Agency Tracking Number:
0539234
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
Los Gatos Research
67 East Evelyn Avenue, Mountain View, CA, 94041
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
An-Dien Nguyen
Dr
(650) 965-3459
a.d.nguyen@algrinc.com
Business Contact:
Anthony Okeefe
Mr
(650) 965-7772
aoklgr@ix.netcom.com
Research Institution:
n/a
Abstract
This Small Business Innovation Research (SBIR) Phase I project will support the development of an automated structural health monitoring sensor system with wireless data acquisition capability, capable of detecting crack, corrosion, and disbonding in metal structures and advanced materials. This novel sensor technology offers a number of advantages including compactness (0.5mm x 2mm x 5mm), lightweight (few grams), and low power consumption (battery powered). This is achieved by fabricating Bragg gratings on stress-wave-sensitive polymer planar waveguides, which is capable of detecting both surface and below surface cracks in advanced material structures. In Phase I, a Lamb wave method is used to demonstrate the polymer gratings' capability to measure stress waves indicating the presence and severity of damages caused by cracks, fiber delaminations, or corrosion in a fiber composite structure, when the structure is probed by an ultrasonic wave generation actuator device. This novel Lamb wave sensor system will offer significant cost saving for the civil and aerospace industries by providing a cost-effective solution for damage detection in large aerospace and civil structures. The new sensor technology will enhance public safety as a result of effective warning systems. Advances in the Lamb wave sensor technology will permit researchers to utilize this technology to better understand degradation mechanism leading to material failure in large and complex structures.

* information listed above is at the time of submission.

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