Weld defect localization in friction stir welding process

被引：7

作者：

Mishra, Debasish ^{[1
]}

Shree, Sristi ^{[3
]}

Gupta, Abhinav ^{[4
]}

Priyadarshi, Ashok ^{[5
]}

Das, Sarthak M. ^{[6
]}

Pal, Surjya K. ^{[7
]}

Chakravarty, Debashish ^{[8
]}

Pal, Srikanta ^{[4
]}

Chattopadhyay, Tanushyam ^{[2
]}

Pal, Arpan ^{[2
]}

机构：

[1] Indian Inst Technol Kharagpur, Adv Technol Dev Ctr, Kharagpur, W Bengal, India

[2] Tata Consultancy Serv, TCS Res & Innovat, Kolkata, India

[3] Birla Inst Technol Mesra, Dept Comp Sci & Engn, Mesra, India

[4] Birla Inst Technol Mesra, Dept Elect & Commun Engn, Mesra, India

[5] Birla Inst Technol Mesra, Math & Comp, Mesra, India

[6] Birla Inst Technol Mesra, Informat Technol, Mesra, India

[7] Indian Inst Technol Kharagpur, Dept Mech Engn, Kharagpur, W Bengal, India

[8] Indian Inst Technol Kharagpur, Dept Min Engn, Kharagpur, W Bengal, India

来源：

WELDING IN THE WORLD | 2021年 / 65卷 / 03期

关键词：

Mother wavelet selection; Friction stir welding; Force signals; Defect identification; ACOUSTIC-EMISSION; SIGNALS; IDENTIFICATION;

D O I：

10.1007/s40194-020-01028-5

中图分类号：

TF [冶金工业];

学科分类号：

0806 ;

摘要：

The article attempts to detect the defects in friction stir welding (FSW) process by analyzing the signal acquired during welding. The said welding technique utilizes pressure and heat developed by the usage of a non-consumable tool. Thus, the axial force signal carries a lot of information about the physical process, and hence, it could be used to identify the weld defects. Signal analysis has been performed by using wavelet-based techniques. Before this analysis, a methodology has been followed to select the best mother wavelets suitable for the signal. The results of defect identification have been validated by mapping the processed signal with the actual weld quality.

引用

页码：451 / 461

页数：11

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