Online detection method of weld penetration based on molten pool morphology and metallic vapor radiation for fiber laser welding

Online detection method of weld penetration based on molten pool morphology and metallic vapor... A novel detection method of penetration status was presented for a high-power fiber laser welding. The metallic vapor and molten pool was recorded by a high-speed camera during welding process. The radiation intensity of metallic vapor, as well as the morphology of molten pool end, was calculated by image processing algorithm as image features. Four image features, the radiation intensity of metallic vapor (RIMV), the area of molten pool end (AMPE), the rear angle of molten pool end (RAMPE), and the aspect ratio of molten pool end (ARMPE), were extracted. The mean value, relative range, variation coefficient, and frequency ratio were computed for the four features to obtain the 16 characteristic parameters. Aiming at penetration status, the characteristic parameters were reorganized to form two complex indicators by the principal component analysis. Experimental results showed that the detection method was potential for online detection on the penetration status in a high-power laser welding process. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The International Journal of Advanced Manufacturing Technology Springer Journals

Online detection method of weld penetration based on molten pool morphology and metallic vapor radiation for fiber laser welding

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Publisher
Springer London
Copyright
Copyright © 2017 by Springer-Verlag London
Subject
Engineering; Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design
ISSN
0268-3768
eISSN
1433-3015
D.O.I.
10.1007/s00170-017-0129-0
Publisher site
See Article on Publisher Site

Abstract

A novel detection method of penetration status was presented for a high-power fiber laser welding. The metallic vapor and molten pool was recorded by a high-speed camera during welding process. The radiation intensity of metallic vapor, as well as the morphology of molten pool end, was calculated by image processing algorithm as image features. Four image features, the radiation intensity of metallic vapor (RIMV), the area of molten pool end (AMPE), the rear angle of molten pool end (RAMPE), and the aspect ratio of molten pool end (ARMPE), were extracted. The mean value, relative range, variation coefficient, and frequency ratio were computed for the four features to obtain the 16 characteristic parameters. Aiming at penetration status, the characteristic parameters were reorganized to form two complex indicators by the principal component analysis. Experimental results showed that the detection method was potential for online detection on the penetration status in a high-power laser welding process.

Journal

The International Journal of Advanced Manufacturing TechnologySpringer Journals

Published: Feb 22, 2017

References

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