Wavelet transform analysis of acoustic emission in monitoring friction stir welding of 6061 aluminum

In this paper, acoustic emission (AE) signals are detected and preliminarily analyzed in order to investigate the possibility of applying the AE technique for the in-process monitoring of an entire friction-stir-welding (FSW) process. Experimental tests are carried out using a high-speed rotating tool traversing on two, butted 6061 aluminum alloy plates with three equally spaced gaps made of two notches aligned along the butting joint of the parts. The wavelet transform (WT) is used to decompose the AE signal into various discrete series of sequences over different frequency bands. There are significant sudden changes in the band energy at the moment when the probe penetrates into and pulls out of the weld joint, as well as when the shoulder makes contact with or detaches from the plates. The band energy variation during the traversing of the tool over the defected region reflects the existence, location, and size of the weld defects. A three-dimensional representation of band energy vs time and scale gives valuable information on the potential weld defects during friction stir welding. Coupled with a contour mapping, the representation can be effectively utilized for monitoring the transient welding state and quickly identifying gap defects.