Computer-Aided Recognition of Defects in Welded Joints during Visual Inspections Based on Geometric Attributes

Computer-Aided Recognition of Defects in Welded Joints during Visual Inspections Based on Geometric Attributes

Bibliographic Details
Parent link:Russian Journal of Nondestructive Testing
Vol. 56, iss. 3.— 2020.— [P. 259-267]
Main Author: Muravyov (Murav’ev) S. V. Sergey Vasilyevich
Corporate Author: Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники Отделение автоматизации и робототехники
Other Authors: Pogadaeva E. Yu. Ekaterina Yurjevna
Summary:Title screen
An automated defect recognition algorithm is presented for detecting and classifying weld defects by photographic images. The proposed recognition algorithm selects a defective domain in a segmented image, extracts geometric features from the image, and relates the defect to one of six classes: no defect, cavity, longitudinal crack, transverse crack, burn-through, or multiple defect. The algorithm is implemented in the Matlab 2018b MathWorks environment and has been tested on 60 photographs of defects of various classes; the accuracy of recognition was 85%.
Режим доступа: по договору с организацией-держателем ресурса
Published: 2020
Subjects:
электронный ресурс
труды учёных ТПУ
weld
defect
segmentation
classification
image processing
visual inspection
сварные швы
дефекты
сегментация
обработка изображений
Online Access:https://doi.org/10.1134/S1061830920030055
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=662251

Internet

https://doi.org/10.1134/S1061830920030055

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