Mr. Dustin T. Thomas Profile

Dustin T. Thomas

at Air Force Research Lab

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Author

Publications (2)

Proceedings Article | 17 May 2005 Paper

Monitoring fatigue crack growth in 7075 T6 aluminum using continuous sensor

G. Grandhi, F. Nkrumah, M. Sundaresan, J. Kemerling, D. Thomas

Proceedings Volume 5764, (2005) https://doi.org/10.1117/12.600165

KEYWORDS: Sensors, Acoustic emission, Aluminum, Interference (communication), Structural health monitoring, Signal detection, Signal processing, Wave plates, Digital filtering, Transducers

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Proceedings Article | 21 July 2004 Paper

Corrosion damage detection with piezoelectric wafer active sensors

Dustin Thomas, John Welter, Victor Giurgiutiu

Proceedings Volume 5394, (2004) https://doi.org/10.1117/12.541152

KEYWORDS: Corrosion, Wave plates, Signal attenuation, Semiconducting wafers, Active sensors, Transducers, Aluminum, Damage detection, Waveguides, Composites

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Since today's aging fleet is intended to far exceed their proposed design life, monitoring the structural integrity of those aircraft has become a priority issue for today's Air Force. One of the most critical structural problems is corrosion. In fact the KC-135 now costs $1.2 billion a year to repair corrosion. In this paper, we plan to show the use of Lamb waves to detect material loss in thin plates representative of aircraft skins. To do this we will use embedded transducers called Piezoelectric Wafer Active Sensor (PWAS) in a pitch-catch configuration. The sensors were placed on a grid pattern. Material loss through corrosion was simulated by removing the material mechanically with an abrasive tool. Thus, simulated corrosion pits of various depths and area coverage were made. Three-count tone burst wave packets were used. The Lamb wave packets were sent in a pitch-catch mode from one transmitter PWAS to the other PWAS in the grid acting as receivers. The Lamb wave mode used in these experiments was A₁, since this was found to be more sensitive to changes due to material loss. At the frequencies considered in our experiments, the A₁ waves are highly dispersive. It was found that, as the Lamb wave travels through simulated corrosion damage, the signal changes. The observed changes were in the signal wavelength (due to change in the dispersive properties of the medium) and in signal amplitude (due to redistribution of energy in the wave packet). This change in signal can be correlated to the magnitude of damage. To achieve this, we have used several approaches: (a) direct correlation between the sent and the received signals; (b) wavelet transform of the signal followed by correlation of the wavelet coefficients time-frequency maps; (c) Hilbert transform of the signal to produce the signal envelope and comparison of the resulting envelope signals (d) neural network correlation between the sent and received signals. It was found that these methods work well together in a complementary way.

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