Information Acquirement of Arc Welding Process

Abstract

Precise image processing algorithm is important for welding process control. Generally, original image cannot be directly used due to the disturbance from welding equipment. Moreover, fluctuation in welding current and arc light also lead to image degrading. All the above factors add difficulties to the image processing, and the image processing algorithms are required to be adaptive to different conditions. In this chapter, both 2D and 3D image processing methods are described. The 2D image processing methods used in this chapter include degrading image recovery, integral edge detection, projection, neural network edge identification and curve fitting to extract the length and width of the weld pool. 3D image processing methods include experimental and SFS(Shape-from-Shading) method to extract topside height of the weld pool. And image processing software exclusively for weld pool images is introduced at the end of the chapter. Real time control of weld pool dynamics is crucial for welding quality, which depends primarily on extracting and calculating geometric characteristics of the weld pool [1-4]. The weld pool contains abundant information about the welding process. Actually, in practice, a skilled welder can estimate the appearance of backside of weld pool by observing the shape, size and dynamic change of the topside of the weld pool and adjust accordingly. Image processing is aimed to obtain the relevant information by enhancing the necessary image features and suppressing undesired distortions. However, many disturbances, such as alternating magnetic field and the relative motion between CCD and weld pool, will affect the information acquirement. Therefore, image processing technology is necessary for the welding process.