A review of implementation of Artificial Intelligence systems for weld defect classification

被引：10

作者：

Vishal, V. ^{[1
]}

Ramya, R. ^{[1
]}

Srinivas, P. Vinay ^{[1
]}

Samsingh, R. Vimal ^{[1
]}

机构：

[1] Sri Sivasubramaniya Nadar Coll Engn, Dept Mech Engn, Chennai 603110, Tamil Nadu, India

来源：

MATERIALS TODAY-PROCEEDINGS | 2019年 / 16卷

关键词：

Welding; Defect Classification Systems; Non-Destructive Testing;

D O I：

10.1016/j.matpr.2019.05.131

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Several methodologies have emerged over the years to enable testing of welded joints. The destructive methods of testing have largely been replaced by Non-Destructive technology today, as this type of testing enables continuous and in-service monitoring and is the basis of preventive maintenance and service of welded structures. Several methods can be used to test these joints and this has been the focus of considerable research work in the field. This review paper compares and contrasts the existing literature on various testing methodologies employed for defect classification of welded joints. (C) 2019 Published by Elsevier Ltd.

引用

页码：579 / 583

页数：5

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