A spectroscopic method based on support vector machine and artificial neural network for fiber laser welding defects detection and classification-Reference-Cited by-同舟云学术

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A spectroscopic method based on support vector machine and artificial neural network for fiber laser welding defects detection and classification

Published:2019-12 Issue: Volume:108 Page:102176
ISSN:0963-8695
Container-title:NDT & E International
language:en
Short-container-title:NDT & E International

Author:

Chen Yuanhang,Chen Bo,Yao Yongzhen,Tan Caiwang,Feng Jicai

Funder

National Key Research and Development Program of China

Shandong Provincial Natural Science Foundation

Shandong Provincial Key Research and Development Program

Publisher

Elsevier BV

Subject

Mechanical Engineering,Condensed Matter Physics,General Materials Science

Reference25 articles.

1. Research of lap gap in fiber laser lap welding of galvanized steel;Fan;Chin J Lasers,2014

2. Nondestructive testing handbook: infrared and thermal testing;Maldague,2001

3. Infrared sensor for top face monitoring for weld pools : measurement Sceince and Technology;Bicknell;Meas Sci Technol,1994

4. Detection of weld pool width using infrared imaging during high-power fiber laser welding of type 304 austenitic stainless steel;Chen;Int J Adv Manuf Technol,2014

5. Predicting weld bead width and depth of penetration from infrared thermal image of weld pool using artificial neural network;Chokkalingham;Insight Non-Destr Test Cond Monit,2012

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