On the example of aluminum alloy AMg5 м plastic deformation and fracture under static loading was investigated. For the material being loaded, a stage of linear hardening, two stages of parabolic hardening and a fracture stage were identified. A change in the form of acoustic emission signals was established with a change in the region of strain hardening. The plastic yielding in the first region was accompanied by the formation of an acoustic emission peak, which was replaced in the next stage by high-amplitude oscillations. Further, for the region of discontinuous yielding, bursts of signals of different amplitude were observed, reflecting the dynamics of the formation of localized deformation bands. The change in the acoustic emission signals reflected the evolution of the deformation hardening processes. To describe the effect of the stagedness of deformation processes on the parameters of acoustic emission, the initial acoustic-emission signal was divided into separate time blocks. To each of these blocks, a discrete wavelet transform was applied. It characterized the time dependence of the waveform on the specific section of the strain hardening curve corresponding for each block. The obtained wavelet decomposition coefficients were processed using principal component analysis. They were plotted on the plane of the first principal components. The points of the multidimensional space corresponded to different regions were divided into partially overlapping clusters. The results of the work showed that the wavelet decomposition coefficients of acoustic emission signal could be used for diagnostics of the stages of strain hardening in aluminum alloys.
The acoustic emission method was applied to study aluminum-magnesium alloys produced by friction stir welding. Alloy specimens were tested under static tension with simultaneous recording of acoustic emission, applied load, and elongation. The recorded acoustic emission signals were processed using projection methods of multivariate data analysis; the informative features used were the coefficients of wavelet discrete decomposition which characterize the low-frequency form of the signal. It is shown that the proposed approach allows the partition of signals formed on different stages of plastic deformation and fracture. Strong differences in acoustic emission signals were revealed and described to be due to the formation of highly defect structure in the weld zones in different welding modes. The obtained results can be useful for acoustic emission diagnostics of welded joints in structures of metal alloys exposed to external loads.
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