1. Tight butt joint weld detection based on optical flow and particle filtering of magneto-optical imaging
- Author
-
Deyong You, Xiangdong Gao, Zhuman Li, and Ling Mo
- Subjects
0209 industrial biotechnology ,Materials science ,Optical flow ,Aerospace Engineering ,02 engineering and technology ,Welding ,Tracking (particle physics) ,law.invention ,020901 industrial engineering & automation ,Optics ,law ,Vertical direction ,0202 electrical engineering, electronic engineering, information engineering ,Magneto ,Civil and Structural Engineering ,Electromagnet ,business.industry ,Mechanical Engineering ,020208 electrical & electronic engineering ,Laser beam welding ,Structural engineering ,Computer Science Applications ,Control and Systems Engineering ,Signal Processing ,Butt joint ,business - Abstract
It is a challenge to detect the weld position during tight butt joint laser welding in that the tight butt joint is non-grooved and invisible. This paper proposes a novel method for tight butt joint weld detection based on magneto optical imaging. Two pieces of weldment were magnetized by an electromagnet so that they could show magnetic N and S polarity respectively. When a polarized light was projected on a magneto-optical film, it would deflect due to magneto-optical effect. In accordance with magneto field distribution, an image formed on the visual sensor. A transition zone of magnetic field distribution which corresponded to the butt joint could be shown in a magneto optical image of weldment. Variation features of magnetic field distribution were obtained by using image sequence optical flow method, and a particle filter was integrated to make an accurate prediction on weld position. Weld position was obtained by calculating the maximum value of optical flow intensity in the vertical direction, and a particle filter was used to realize the accurate prediction on weld position. Experimental results showed that the proposed method was effective in detection of weld and realizing weld seam tracking.
- Published
- 2017