Dr. Mary Ann F. Harrison Profile

Dr. Mary Ann F. Harrison

Scientist at WVHTC Foundation

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Author

Publications (5)

Proceedings Article | 31 May 2013 Paper

Ear recognition: a complete system

Ayman Abaza, Mary Ann Harrison

Proceedings Volume 8712, 87120N (2013) https://doi.org/10.1117/12.2015946

KEYWORDS: Ear, Databases, Feature extraction, Binary data, Image segmentation, Principal component analysis, Biometrics, Facial recognition systems, Wavelet transforms, Error analysis

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Proceedings Article | 16 May 2007 Paper

Acoustic leak-detection system for railroad transportation security

P. Womble, J. Spadaro, M. Harrison, A. Barzilov, D. Harper, L. Hopper, E. Houchins, B. Lemoff, R. Martin, C. McGrath, R. Moore, I. Novikov, J. Paschal, S. Rogers

Proceedings Volume 6538, 653817 (2007) https://doi.org/10.1117/12.718541

KEYWORDS: Sensors, Acoustics, Video, Transducers, Cameras, Signal detection, Prototyping, Gases, Inspection, Optical inspection

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Proceedings Article | 31 March 2006 Paper

Utilizing chaotic excitation of microelectromechanical systems (MEMS) for microstructure fault detection

J. M. Dawson, M. A. F. Harrison, C. A. Maxey, W. B. McCormick, L. A. Hornak

Proceedings Volume 6172, 617219 (2006) https://doi.org/10.1117/12.658534

KEYWORDS: Microelectromechanical systems, Motion measurement, Time series analysis, Resonators, Data modeling, Nondestructive evaluation, Sensors, Distortion, Control systems, Etching

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Proceedings Article | 20 March 2006 Paper

Fiber optic strain monitor for an uninhabited aerial vehicle

Thomas Owens, Philip Pesavento, Robert Ice, Steven Knudsen, Mary Ann Harrison

Proceedings Volume 6176, 61761G (2006) https://doi.org/10.1117/12.658778

KEYWORDS: Unmanned aerial vehicles, Intelligence systems, Sensors, Fiber optics, Data acquisition, Structural health monitoring, Control systems, Composites, Signal processing, Fiber optics tests

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The Institute for Scientific Research (ISR) and the Naval Research Laboratory (NRL) will build and operate portable real-time fiber Bragg grating interrogator systems for monitoring strain in ISR's Multi-Modal Sensor (MMS) uninhabited aerial vehicle (UAV). ISR's UAV is constructed of fiberglass composites with aluminum stiffeners. The cargo bay and on-board electronics are intended to accommodate a variety of compact sensors. Because of the small size of the UAV, weight and volume are restricted, necessitating considerable redesign of laboratory interrogators to meet UAV constraints. NRL will be supplying a multiplexed interrogator for monitoring structural response rates in the UAV up to about 2 kHz, while ISR will develop an optical frequency domain reflectometer (OFDR) for measuring lower frequency response of large numbers of gratings below about 100 Hz. The OFDR system will test a special differencing technique to separate strain induced signals from environmentally induced signals. A National Instruments CompactRIO system with a 3 million gate FPGA and a 200 MHz Pentium processor is being used for real-time data acquisition and onboard signal analysis. The CompactRIO system weighs about 1.6 kg, measures 18cm x 9cm x 9cm, consumes less than 5 W of power, and withstands over 50g of shock. Lithium polymer batteries will be used to power the system for flight times up to about one hour in the present configuration. While the near-term objective of this project is to overcome the challenges of applying fiber-optic strain monitors to aerial vehicles, the longer-term objective is to develop a system for detecting damage in aerial vehicles using chaotic attractor based methods. One of the key issues in damage detection by this means revolves around the ability to use the chaotic excitation of the airframe from random aerodynamic vortices to detect the onset of composite degradation. There is evidence that attractor based methods applied to these ambient chaotic vibrations will provide a very sensitive indication of damage.

Proceedings Article | 20 March 2006 Paper

A comparison of time series analysis algorithms for detection of barely visible impact damage in UAV wings

Mary Ann Harrison, Steven Knudsen, Mark Seaver, Jonathan Nichols, Steve Trickey, Louis Pecora, Daniel Pecora

Proceedings Volume 6176, 61760B (2006) https://doi.org/10.1117/12.657884

KEYWORDS: Sensors, Unmanned aerial vehicles, Skin, Time series analysis, Composites, Statistical analysis, Manufacturing, Fractal analysis, Fiber Bragg gratings, Stochastic processes

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