The state-of-the-art methodologies for quality analysis of arc welding process using weld data acquisition and analysis techniques

Arc welding, due to its simplicity, ease of use and low maintenance cost is one of the most widely used welding process in almost all types of modern industries. In this process, voltage, current and welding speeds are the major variable which influences the final weld product. Among these, monitoring welding speed is relatively easy, while monitoring voltage and current is not. This is because welding is a stochastic process in which wide variations in voltage and current occurs and durations of these variations are so short that the ordinary ammeters and voltmeters cannot measure these variations. However, using suitable sensors coupled with a high-speed data acquisition system, real time variations taking place in an actual welding process can be recorded and subsequently analyzed. A careful analysis of these variations using various signal processing, statistical and data mining techniques can provide a very useful information in estimating the quality of final weld product. In this research, a first of its kind, detailed review on various aspects of weld monitoring systems used for weld data acquisition and its subsequent analysis are presented. This will include an in-depth analysis of various electronic sensing and data sampling modules which can be used in the design and development of a Weld Monitoring System. Additionally, this review also includes a brief study on various soft computing, data mining and machine learning techniques on weld data in predicting the quality of different welding parameters. Finally, summary of the review is followed by the scope of future research to pave out some of the new dimensions in exploring the multi-disciplinary area of evaluating the arc welding quality using data acquisition and analysis techniques.