Publication

Abstract : Welding is one of the major metal-joining process employed in fabrication industries, especially in manufacturing of boilers and pressure vessels. Control of weld quality is very important for such industries considering the severe operating conditions. Industries are looking for some kind of real-time process monitoring/control that will ensure the weld quality online and prevent the occurrence of defects. In this paper an attempt is made to establish a correlation between the current and voltage signatures with the good weld and weld with porosity and burn through defect during the welding of carbon steel using gas metal arc welding (GMAW) process. Experimental setup has been established and experiments were conducted using a welding robot integrated with GMAW power source. The experimental setup includes online current and voltage sensors, data loggers, and signal processing hardware and software. Welding conditions are carefully designed to produce good weld and weld with defects such as burn through and porosity. Current and voltage signatures are captured using data acquisition system (DAS). Software has been developed to analyze the data captured by the DAS. Statistical methods are employed to study the transient data. The probability density distributions of the current and voltage signature demonstrates a good correspondence between the current and voltage signatures with the welding defect.