#6254. Nondestructive testing algorithm of building concrete material defects based on machine learning

September 2026publication date
Proposal available till 18-05-2025
4 total number of authors per manuscript0 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Control and Optimization;
Control and Systems Engineering;
Information Systems;
Computer Networks and Communications;
Signal Processing;
Artificial Intelligence;
Human-Computer Interaction;
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Abstract:
In order to pay more attention to the quality of construction concrete and accurately judge whether concrete material meets the standard, a nondestructive testing algorithm of building concrete material defects based on machine learning is proposed. Through the ray tracing algorithm of Snell’s theorem, the shortest path between two random punctuation marks of building concrete is calculated. The original coordinate system and grid size were set, the trend and length of the line in the grid were calculated, and the coordinates between the grid corner points and the transmitting probe were calculated so as to obtain the position of the intermediate refractive points of the two probes. Finally, the vector dot product of the local defects is obtained by the optimal hyperplane calculation of the binary classification in the support vector machine.
Keywords:
building concrete materials; image acquisition; Machine learning; nondestructive testing; similarity

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