John Wertz, Chenoa Flournoy, Laura Homa, Tyler Tallman
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引用次数: 0
Abstract
Electrical impedance tomography is a method of mapping the conductivity distribution of a domain. For decades it has been considered a potential in situ nondestructive evaluation technique for characterization of conductivity changes in aerospace composites. Yet, several challenges must be addressed before this technique can be transitioned from the laboratory to meaningful practice; for example, the expense of the inverse problem that must be solved to estimate conductivity. An alternative is to characterize damage from the measured voltage-current relationship using deep learning. In this work, we develop and test a deep learning algorithm to characterize time-independent damage events in complex geometry.
期刊介绍：
MRS Communications is a full-color, high-impact journal focused on rapid publication of completed research with broad appeal to the materials community. MRS Communications offers a rapid but rigorous peer-review process and time to publication. Leveraging its access to the far-reaching technical expertise of MRS members and leading materials researchers from around the world, the journal boasts an experienced and highly respected board of principal editors and reviewers.
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