Application of continuous wavelet transform based on Fast Fourier transform for the quality analysis of arc welding process

SMAW (Shielded Metal Arc Welding) and GMAW (Gas Metal Arc Welding) are two of the most prominent welding processes commonly utilized in almost all types of modern industries. Among various aspects of these processes, some of the important parameters that govern the quality of the final weld product are the skill level of welders, welding consumables, and the role of shielding gases (in GMAW). Currently, the role of these parameters in determining the quality of the welded product is examined by evaluating the final weld produced and not by investigating how these factors affect the welding process. This is an indirect way to evaluate such welding parameters, which are both time-consuming and expensive. During the actual welding process, random variations in arc signals (voltage and current) take place. These dynamic variations are so short and rapid that ordinary ammeters and voltmeters cannot monitor the rate of such variations. However, the reliable acquisition of such variations and its subsequent analysis can provide very useful information in determining the quality of the final weld product. In this study, arc voltage and current were acquired at 100,000 samples/sec, filtered and subsequently analyzed using Continuous Wavelet Transform based on Fast Fourier Transform (CWT-FFT) technique to evaluate welding skill, welding electrodes (in SMAW process), and the effect of shielding gases (in GMAW process). Results thus obtained clearly differentiated the skill level of different trainee welders and welding electrodes in the SMAW process and the effect of shielding gases and arc current in the GMAW process. Very good correlation among the obtained results, its weld bead and its weld pool images were observed. Hence, this research proposes a simple yet effective methodology to evaluate the arc welding process parameters using CWT-FFT analysis of the welding signals.