Machine Learning Applications in Nondestructive Testing of Concrete Structures
Daniel Algernon,
Ingo Münch,
Aurélia Muller
et al.
Abstract:Machine Learning bears great potential for data‐driven solutions in the field of nondestructive testing (NDT) of concrete structures. The analysis of the data collected with NDT methods, such as ultrasonics, impact‐echo and ground penetrating radar, can be complex and requires experience. The expected benefit of Machine Learning applications in this context goes beyond the increase of efficiency obtained by automating the analysis process. While traditional analysis approaches are usually solely based on key f… Show more
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