Classification and identification of surface defects in friction stir welding: An image processing approach

被引:90
作者
Ranjan, Ravi [1 ]
Khan, Aaquib Reza [2 ]
Parikh, Chirag [3 ]
Jain, Rahul [4 ]
Mahto, Raju Prasad [4 ]
Pal, Srikanta [5 ]
Pal, Surjya K. [4 ]
Chakravarty, Debashish [6 ]
机构
[1] Birla Inst Technol, Dept Elect & Commun Engn, Ranchi 835215, Bihar, India
[2] Birla Inst Technol, Dept Elect & Elect Engn, Ranchi 835215, Bihar, India
[3] Birla Inst Technol, Dept Chem Engn, Ranchi 835215, Bihar, India
[4] Indian Inst Technol, Dept Mech Engn, Kharagpur 721302, W Bengal, India
[5] Shiv Nadar Univ, Dept Elect Engn, Gautam Buddha Nagar 201314, India
[6] Indian Inst Technol, Dept Min Engn, Kharagpur 721302, W Bengal, India
关键词
Friction stir welding; Weld defects; Digital image processing; METAL TRANSFER; ALGORITHM;
D O I
10.1016/j.jmapro.2016.03.009
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Friction stir welding (FSW) is a new entrant in welding technology and getting a defect-free weld is the final objective. But different defects are generated due to various reasons and needs to be analyzed to eliminate them. The aim of the research work is to identify and classify different kinds of surface defects generally encountered during the FSW process using digital image processing techniques. The defects on the surface of the weld are identified using image pyramid and image reconstruction algorithms. Further, using these algorithms the defects can be classified into voids, grooves, cracks, key-hole and flash with the help of unique features of each kind of defect. Vertical intensity plot and the area plot of the defect blobs are represented for the proper localization and analysis of severity of defects. (C) 2016 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:237 / 253
页数:17
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