A neural network and multiple regression method for the characterization of the depth of weld penetration in laser welding based on acoustic signatures-Reference-Cited by-同舟云学术

A neural network and multiple regression method for the characterization of the depth of weld penetration in laser welding based on acoustic signatures

Published:2009-05-12 Issue:2 Volume:22 Page:131-143
ISSN:0956-5515
Container-title:Journal of Intelligent Manufacturing
language:en
Short-container-title:J Intell Manuf

Author:

Huang Wei,Kovacevic Radovan

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering,Software

Link

http://link.springer.com/content/pdf/10.1007/s10845-009-0267-9.pdf

Reference20 articles.

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3. Chumakov R. (2008) An artificial neural network for fault detection in the assembly of thread-forming screws. Journal of Intelligent Manufacturing 19: 327–333

4. Farson D., Hillsley K., Sames J., Young R. (1996) Frequency-time characteristics of airborne signals from laser welds. Journal of Laser Applications 8: 33–42

5. Gu H., Duley W.W. (1996a) Resonant acoustic emission during laser welding of metals. Journal of Physics D: Applied Physics 29: 550–555

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