Master of Science in Civil Engineering, University of Toledo, 2014, Civil Engineering

The use of Lamb waves to investigate damage in thin metal plates is investigated. This study is necessary to have a thorough understanding of Lamb wave propagation characteristics, its dispersion phenomena, its behavior when scattered from minor flaws, and its ability to detect damages. Nowadays, there is a growing interest to use Lamb waves for damage detection techniques. A literature review of Lamb waves and other types of waves pertinent to their use in damage detection mechanisms is presented. Dispersion curves for aluminum plates are studied for symmetric and anti-symmetric modes. Detailed comparison between the different modes, and the merits and demerits of these wave modes which help to select an appropriate mode for use in damage detection is also explained. Different types of damage have been detected experimentally using a pitch-catch method and are verified by using Waveform Revealer and finite element software, Pzflex. Based on selected fundamental Lamb wave modes, damage inflicted by drilling a through-thickness hole in an aluminum plate has been detected experimentally using a pitch-catch method by applying mode conversion phenomena and is verified by using Waveform Revealer. Moreover, different sizes of through-thickness holes and cracks in an aluminum plate have been detected by running simulations in Pzflex and using changes in time of flight and amplitude of the wave as parameters. Based on the experimental and simulation results, it is concluded in this paper that Lamb waves are sensitive to cracks and holes in thin aluminum plates, and that these types of defects can be detected by techniques using Lamb waves.

Committee: Douglas Nims Dr. (Advisor); Brian Randolph Dr. (Committee Member); Daniel Georgiev Dr. (Committee Member) Subjects: Engineering

MS, University of Cincinnati, 2003, Engineering : Mechanical Engineering

There is a growing need for the development of in-situ continuous monitoring systems to allow the health monitoring of large structures and the rapid introduction of advanced high performance and heterogeneous materials and combinations of these materials into service. This thesis makes a contribution in the development of artificial neural systems for health monitoring of large and complex structures, and for impact location on targets. The artificial neural system is a passive monitoring system that can minimize the on board instrumentation needed for real-time health monitoring. The system uses highly-distributed interconnected sensor nodes and parallel processing that mimics the hierarchy of the biological neural system to collect dynamic strain signals caused by damage events. The dynamic strains can be in the form of high frequency waves called acoustic emissions caused by damage growth or lower frequency waves and vibration caused by impact to the structure. The artificial neural system processes these dynamic signals and provides an indication of the location and severity of the damage or impact. To verify the approach, an artificial neural system and wave propagation in the panel were modeled. Simulations of damage and impact in a glass fiber composite plate were performed in which the elastic response was computed in closed form at small time steps and the coupled piezoceramic constitutive equations and conductivity equations were also solved. Experimentation was then performed using a glass fiber composite panel and the simulation and experimental results were compared. These studies showed that the artificial neural system is a simultaneously sensitive to low frequency dynamic strains caused by structural vibrations and impact, as well as high frequency acoustic emission signals that accompany damage growth. An important advantage of this new approach is the application of inhibition and firing of the neurons that receive the damage signals. This allows (open full item for complete abstract)

Committee: Dr. Mark J. Schulz (Advisor) Subjects: Engineering, Mechanical