Infrared imaging based machine vision system to determine transient shape of isotherms in submerged arc welding

Abstract

Submerged arc welding (SAW) is one of the important industrial welding processes for heavy industries which include ship building and steel industries. The transient temperature distribution during the welding process has a significant influence on the heat affected zone width, microstructure formation, residual stresses, distortion, and hence on the fatigue behaviour of the welded structures. To accurately determine the transient temperature distribution, the exact shape of the heat source distribution needs to be considered. Machine vision can be a unique method for determination of such transient temperature distribution. In this paper, a machine vision system is developed to determine the transient shape of isotherm of submerged arc welded plates. It is based on infrared imaging to capture and extract the temperature history of the welding process. The transient temperature distribution is observed to be egg shape. The shape of isotherm is analyzed and validated with the experimental data acquired for a wide range of process parameters. These comparisons showed close agreement. The extracted data from the proposed machine vision system is used as the input information for various investigations, such as maximum temperature, isotherm generation, cooling rate plots and image segmentation studies. The developed method is a contactless method. It not only eliminates the possible errors encountered in contact measurement methods, but also provides a user friendly interface and accurate results in less time, and hence significantly reduces the experimental time. This method demonstrated its successful application for submerged arc welding, and furthermore it can be applied for the estimation of transient temperature field in other manufacturing processes.