Assessment of Weld Bead Mechanical Properties During Destructive Testing Using Image Processing by Multivision Technique

Grade 316L stainless steels can be easily welded by all types of fusion welding processes. Pulsed gas metal arc welding (P-GMAW) iswidely used in industries. By melting continuously fed current-carrying wire, P-GMAW achieves coalescence of metals. However, to achieve good quality of weld and attractive looking, P-GMAW needs consistent, high-quality welding procedures. This need is due to continuous control metal transfer that is necessary in P-GMAWfor thin metal workpieces. This paper explores how image processing could be applied in assessment of mechanical properties in destructive testing of SS304L material weld bead. Image features like height, area, perimeter of weld bead have been extracted for different loading conditions using image processing by multivision techniques. The vision techniques play an important role in quality inspection and process monitoring. Multi Vision technology improves the edge recognition, pixel processing and reliable consistently achieved. From the study, it is found that multivision is capable of quantifying the parameters associated with soundness and performance of weld joints, and the established trend using image processing features is correlating well with traditional measurement.