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Ultrasonic thickness measurements using machine learning

Authors: Caleb García (Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional Unidad Saltillo) , Ludivina Facundo (Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional Unidad Saltillo) , Arturo Baltazar (Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional Unidad Saltillo)

  • Ultrasonic thickness measurements using machine learning

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    Ultrasonic thickness measurements using machine learning

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Abstract

Thickness measurements using ultrasonic contact test is a well know nondestructive evaluation technique. However, its implementation in a robotic system with closed-loop feedback control for artificial intelligent measurements requires precise information of positioning and force of the ultrasonic probe. In this work, we describe an ultrasonic probe developed in our lab that uses a semispherical soft membrane made from an elastomer. The aim is to develop a methodology for positioning and force control based on ultrasonic signal information process using sparse matrix optimization and Fourier analysis techniques. The results show that the proposed methodology allows a fine tuning of the probe pose with high sensitivity to load and misalignment to get accurate thickness measurements.

How to Cite:

García, C., Facundo, L. & Baltazar, A., (2019) “Ultrasonic thickness measurements using machine learning”, Review of Progress in Quantitative Nondestructive Evaluation .

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Published on
2019-12-03

Peer Reviewed

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