In structural health monitoring (SHM), impact detection and characterization techniques often focus on identifying parameters of impact such as the location and velocity of an impacting object. A distributed network of sensors is used to passively detect the mechanical wave created by the impact. Various techniques are used to analyze the signals based on time of arrival, amplitude and phase. A simpler architecture could be used to determine whether an impacting event was benign or caused damage and requires further evaluation. This research focuses on detecting attributes of impact-generated elastic wave signals that are indicative of local damage at the impact site. Waveforms deviate insignificantly for undamaged materials, however, when a material is stressed to plastic deformation or damaged the waveform of propagation through the material is noticeably affected. This change in wave speed may be detectable by SHM sensors, and can be used as an indicator of damage. Low velocity impact experiments were conducted on thin aluminum plates instrumented with piezoelectric and magneto-elastic sensors at various locations. The sensors acquired the initial passage of the impact wave signal before reflections off the boundaries became a significant element. By inspecting the signal for deviations induced by damage (such as plastic deformation), a routine for evaluating damage can be inferred. Further work may correlate features of the signal with damage severity providing an extra level of information in determining the next step in evaluating the damage. Using this approach, it may be possible to evaluate impact damage using limited numbers of passive sensors.
- Aerospace Division
Investigation of Low Velocity Impact Damage in Aluminum Alloys
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Cooper, B, & Zagrai, A. "Investigation of Low Velocity Impact Damage in Aluminum Alloys." Proceedings of the ASME 2012 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 1: Development and Characterization of Multifunctional Materials; Modeling, Simulation and Control of Adaptive Systems; Structural Health Monitoring. Stone Mountain, Georgia, USA. September 19–21, 2012. pp. 837-844. ASME. https://doi.org/10.1115/SMASIS2012-8145
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