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Monitoring and processing the acoustic emission signals from the friction-stir-welding process

Abstract This paper discusses the detection and analysis of the acoustic emission (AE) signals to investigate the possibility of applying the AE technique for the in-process monitoring of the friction-stir-welding process. Tests are carried out for joining similar and dissimilar metals using a high-speed rotating tool under various rotational speeds and traverse speeds and for different tool penetration depths. The results of fast Fourier transform show that the amplitude of the AE signal in the frequency domain is sensitive to the change in the depth of penetration of the tool. Signals in certain frequency ranges disappear when the tool loses contact with the workpiece during the process. Discrete wavelet transform indicates significant sudden changes in the decomposed signal in the lower frequency ranges (higher levels) when the shoulder makes contact with or detaches itself from the workpieces. By identifying the frequencies during the process and analysing the wavelet decomposed signals in various levels or frequency bands, it is possible to monitor effectively the transient welding state and to identify quickly 2the process changes.