Performance Evaluation of Arc Welding Process Using Weld Data Analysis

Abstract

Shielded metal arc welding (SMAW) and metal inert gas (GMAW) welding process are the two most widely used welding processes. These processes are widely used for the construction and fabrication purpose in almost all type of industries. Some of the important factors which govern the weld quality in these welding processes are welding power sources, role of shielding gas (for GMAW process), welding consumables and skill of the welders. Currently, effects of these factors are evaluated by examining the quality of the weld produced and not by monitoring how welding process is affected by change in these factors. This is an indirect method because actual contribution made by individual parameter in physical process is effectively ignored. Further, this is expensive and time-consuming as the assessment can be carried out only after the weld is completed. Hence, a procedure to assess the quality of welding process using the data acquired while welding is in progress is preferred to testing of the weld for this purpose. In both SMAW and GMAW processes, welding speed, voltage and current are important parameters that affect the quality of the welds. Among these, monitoring of welding speed is relatively easy; but monitoring voltage and current is not. This is because, welding is a stochastic process in which wide variation in voltage and current occurs and duration of these variations is so short that they are not observed in the voltage and current displayed in the power source. However, with the help of a high-speed data acquisition system, voltage and current variations during actual welding process can be recorded and subsequently analysed to reveal very useful information on the welding process, and subsequently quality analysis of individual welding parameters can also be done. In the present study, the voltage and current signals acquired using a digital storage oscilloscope have been used to study SMAW and GMAW processes. Data was acquired for duration of 20 s at a sampling rate of 100,000 samples/s while welding is in progress. In the case of SMAW process, welding data was acquired for welds made using different welding power sources, but with same welder and same type of electrode. In the case of GMAW process, welds were made using same wire and same welder but with different gases for shielding and at different set currents. Dynamic variation in the voltage and current signals were carefully studied using time domain and statistical analyses. Results showed that differences in the characteristics of the different power sources used for SMAW process and effect of shielding gases and arc current on GMAW process could be easily revealed by such analysis. For SMAW process, results obtained could also be correlated with the appearance of the weld beads. Hence, a procedure involving high-speed data acquisition of voltage and current signal while welding is in progress and the statistical analysis of the acquired data have been proposed for monitoring of these two arc welding processes.