In‐process gap detection in friction stir welding

Purpose – This paper aims to investigate methods of implementing in‐process fault avoidance in robotic friction stir welding (FSW).Design/methodology/approach – Investigations into the possibilities for automatically detecting gap‐faults in a friction stir lap weld were conducted. Force signals were collected from a number of lap welds containing differing degrees of gap faults. Statistical analysis was carried out to determine whether these signals could be used to develop an automatic fault detector/classifier.Findings – The results demonstrate that the frequency spectra of collected force signals can be mapped to a lower dimension through discovered discriminant functions where the faulty welds and control welds are linearly separable. This implies that a robust and precise classifier is very plausible, given force signals.Research limitations/implications – Future research should focus on a complete controller using the information reported in this paper. This should allow for a robotic friction stir ...