Edge detection for aluminum alloy MIG welding pool based on pulse coupled neural network

Author

Wu Mingliang ; Zhang Gang ; Huang Jiankang ; Shi Yu ; Shao Ling

Author_Institution

Sch. Of Mech. & Electron. Eng., Lanzhou Univ. of Technol., Lanzhou, China

Volume

2

fYear

2011

fDate

26-28 July 2011

Firstpage

691

Lastpage

694

Abstract

Aimed at the problem of detection of pool edge for aluminum alloy MIG welding, a new method is adopted. The method is used to detect the pool edge of aluminum alloy MIG welding by applying the pulse coupled neural networks algorithm. The pulse coupled neural networks algorithm is introduced in this paper. The detection of pool edge for MIG welding pool is carried out with this algorithm by MATLAB. Then, the comparison between the result of PCNN algorithm and Canny detector is completed. The result indicates that the pulse coupled neural networks algorithm can be used to detect the process image of welding pool. And the image of pool edge by using the pulse coupled neural networks algorithm is clear and consistent. Besides, this new method can effectively overcome the influence of noise from welding pool image. The time of single frame processing is 54 ms.

Keywords

aluminium alloys; arc welding; edge detection; image denoising; neural nets; production engineering computing; Canny detector; MATLAB; MIG welding pool; PCNN algorithm; aluminum alloy; edge detection; image denoise; pulse coupled neural network; Entropy; Image edge detection; Image segmentation; Mathematical model; Neurons; Noise; Welding; Edge detection of welding pool; aluminum alloy MIG welding; pulse coupled neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2011 Seventh International Conference on

Conference_Location

Shanghai

ISSN

2157-9555

Print_ISBN

978-1-4244-9950-2

Type

conf

DOI

10.1109/ICNC.2011.6022144

Filename

6022144