A quality diagnosis method of GMAW based on improved empirical mode decomposition and extreme learning machine-Reference-Cited by-同舟云学术

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A quality diagnosis method of GMAW based on improved empirical mode decomposition and extreme learning machine

Published:2020-06 Issue: Volume:54 Page:120-128
ISSN:1526-6125
Container-title:Journal of Manufacturing Processes
language:en
Short-container-title:Journal of Manufacturing Processes

Author:

Huang Yong,Yang Dongqing,Wang Kehong,Wang Lei,Fan Jikang

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Reference27 articles.

1. On-line quality monitoring in short-circuit gas metal arc welding;Adolfsson;Weld J NEW YORK,1999

2. A statistical approach for monitoring stochastic welding processes;Alfaro;J Mater Process Technol,2006

3. Evaluation of welding skill using probability density distributions and neural network analysis;Kumar;Measurement,2018

4. Statistics of signature images for arc welding fault detection;Simpson;Sci Technol Weld Join,2013

5. Signature image stability and metal transfer in gas metal arc welding;Simpson;Sci Technol Weld Join,2008

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