A Novel Wireless System for Structural Integrity Monitoring of Aircraft

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$100,000.00
Award Year:
2002
Program:
SBIR
Phase:
Phase I
Contract:
N68335-02-C-3105
Agency Tracking Number:
N01-174-03
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
Intelligent Automation, Inc.
7519 Standish Place, Suite 200, Rockville, MD, 20855
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
161911532
Principal Investigator:
Chiman Kwan
Director of R&D
(301) 222-0444
ckwan@i-a-i.com
Business Contact:
marc Toplin
Director of Contracts
(301) 222-0444
mtoplin@i-a-i.com
Research Institution:
n/a
Abstract
"Intelligent Automation, Incorporated (IAI) and its subcontractor, Penn State U., propose a novel system to detect damage in aircraft structures. The system combines a novel wireless sensor for signal acquisition and a robust software for fault prognosis.The sensor is known as SAW-IDT (Surface Acoustic Wave Interdigital Transducer). It is low cost, passive, compact, and can be operated in a wireless manner. The sensor has been proven to be useful for sensing cracks in rivet holes. Other structural defectssuch as corrosion, delamination, fatigue cracking can also be detected. 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, including some use for equipment diagnostics. However, unlikeconventional usage of HMM for fault isolation, 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 beeasily embedded into the structure. The ability to predict the onset of structural failures is critical for reducing cost and improving safety in aircraft. At the end of Phase 2, we will have a

* information listed above is at the time of submission.

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