Guided Wave Structural Health Monitoring with Environmental Considerations

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Virginia Tech

Damage detection in mechanical and aerospace structures is critical to maintaining safe and optimal performance. The early detection of damage increases safety and reduces cost of maintenance and repair. Structural Health Monitoring (SHM) integrates sensor networks and structures to autonomously interrogate the structure and detect damage. The development of robust SHM systems is becoming more vital as aerospace structures are becoming more complex. New SHM methods that can determine the health of the structure without using traditional non-destructive evaluation techniques will decrease the cost and time associated with these investigations. The primary SHM method uses the signals recorded on a pristine structure as a reference and compares operational signals to the baseline measurement. One of the current limitations of baseline SHM is that environmental factors, such as temperature and stress, can change the system response so the algorithm indicates damage when there is none. Many structures which can benefit from SHM have multiple components and often have connections and interfaces that also can change under environmental conditions, thus changing the dynamics of the system.

This dissertation addresses some of the current limitations of SHM. First the changes that temperature variations and applied stress create on Lamb wave propagation velocity in plates is analytically modeled and validated. Two methods are developed for the analytical derivative of the Lamb wave velocity; the first uses assumes a thermoelastic material while the second expands thermoelastic theory to include thermal expansion and the associated stresses. A model is developed so the baseline measurement can be compensated to eliminate the false positives due to environmental conditions without storage of dispersion curves or baseline signals at each environmental state. Next, a wave based instantaneous baseline method is presented which uses the comparison of simultaneously captured real time signals and can be used to eliminate the influence of environmental effects on damage detection. Finally, wave transmission and conversion across interfaces in prestressed bars is modeled to provide a better understanding of how the coupled axial and flexural dynamics of a non-ideal preloaded interface change with applied load.

thermal sensitivity, Lamb waves, guided waves, environmental factors, structural health monitoring