Inline Defective Laser Weld Identification by Processing Thermal Image Sequences with Machine and Deep Learning Techniques

Inline Defective Laser Weld Identification by Processing Thermal Image Sequences with Machine and Deep Learning Techniques

The non-destructive testing methods offer great benefit in detecting and classifying the weld defects. Among these, infrared (IR) thermography stands out in the inspection, characterization, and analysis of the defects from the camera image sequences, particularly with the recent advent of deep lear...

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Bibliographic Details
Main Authors: Domenico Buongiorno, Michela Prunella, Stefano Grossi, Sardar Mehboob Hussain, Alessandro Rennola, Nicola Longo, Giovanni Di Stefano, Vitoantonio Bevilacqua, Antonio Brunetti
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Applied Sciences
Subjects:
industrial quality control
weld defect detection
intelligent diagnostic systems
thermography
machine learning
deep learning
Online Access:https://www.mdpi.com/2076-3417/12/13/6455

Internet

https://www.mdpi.com/2076-3417/12/13/6455

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