Probing weld quality monitoring in friction stir welding through characterization of signals by fractal theory

被引：9

作者：

Das, Bipul ^{[1
]}

Bag, Swarup ^{[1
]}

Pal, Sukhomay ^{[1
]}

机构：

[1] Indian Inst Technol Guwahati, Dept Mech Engn, Gauhati 781039, Assam, India

来源：

JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY | 2017年 / 31卷 / 05期

关键词：

Fractal; Monitoring; Higuchi; Katz; Weld quality; ARTIFICIAL NEURAL-NETWORKS; ALUMINUM-ALLOY; MECHANICAL-PROPERTIES; ACOUSTIC-EMISSION; VISION SENSOR; SEAM TRACKING; GAP DETECTION; PURE COPPER; PARAMETERS; JOINTS;

D O I：

10.1007/s12206-017-0444-2

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

Providing solutions towards the improvisation of welding technologies is the recent trend in the Friction stir welding (FSW) process. We present a monitoring approach for ultimate tensile strength of the friction stir welded joints based on information extracted from process signals through implementing fractal theory. Higuchi and Katz algorithms were executed on current and tool rotational speed signals acquired during friction stir welding to estimate fractal dimensions. Estimated fractal dimensions when correlated with the ultimate tensile strength of the joints deliver an increasing trend with the increase in joint strength. It is observed that dynamicity of the system strengthens the weld joint, i.e., the greater the fractal dimension, the better will be the quality of the weld. Characterization of signals by fractal theory indicates that the single-valued indicator can be an alternative for effective monitoring of the friction stir welding process.

引用

页码：2459 / 2465

页数：7

共 37 条

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