NDLI: Seam sensing of multi-layer and multi-pass welding based on grid structured laser

Content Provider	Springer Nature Link
Author	Zhang, Chenghao Li, Haichao Jin, Zeshi Gao, Hongming
Copyright Year	2016
Abstract	Multi-layer and multi-pass welding is widely used in some fields such as shipbuilding and boiler manufacturing. However, single line structured laser is insufficient to obtain the position and pose of the finished welding seams and predict next welding seam after based layer welding had been completed. In this paper, a new vision sensing method which uses grid structured laser for weld seam sensing is presented. It detects the previous weld beads to predict the following welding path position of the next layer. Based on image capturing and image processing algorithm, a high-quality image with distorted grid is obtained. Since extracting feature points from distorted grid structured laser is much more difficult than that from single line structured laser, a robust algorithm is proposed. Through calibrating and calculating of coordinate conversion, the position data of seams is determined in the world Cartesian coordinate system. The detecting and scanning experiments are ultimately performed, which prove that the seam sensing method is feasible and effective.
Starting Page	1103
Ending Page	1110
Page Count	8
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	91
Issue Number	1-4
e-ISSN	14333015
Language	English
Publisher	Springer London
Publisher Date	2016-12-01
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Multi-layer and multi-pass weld Grid structured laser Image processing Weld seam calibration Industrial and Production Engineering Media Management Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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