Simple monitoring of welding spatter for quantification and observation using a mobile phone

Abstract

Unstable welding arcs can cause the scattering of molten welding pools, a phenomenon known as welding spatter. Spatter deteriorates product quality and necessitates inefficient secondary processes and their associated costs for its removal. Image processing studies aiming to reduce spatter have been performed, but little effort has been devoted to studying the behavior of and quantifying spatter. Furthermore, most studies use a high-speed camera to obtain welding spatter images; however, expensive high-speed cameras are not suited to practical industrial uses. In this study, the distribution of metal inert gas welding spatters is quantified and obtained using a mobile phone camera. LabVIEW vision modules are used to establish welding spatter monitoring algorithms. The mobile phone camera is installed vertically and horizontally. Sequential images are obtained to analyze welding spatter color and shape data. Vertical welding spatter images are converted to gray scale and the color range is analyzed. Welding spatter shape is extracted through the conversion to grayscale images, and welding spatter distribution is secured by tracking welding spatter shape. With this technique, spatter can be used as an index for exterior quality. Furthermore, these results can be used to measure and reduce fundamental spatter in automated welding lines.