Wavelet based harmonics decomposition of ultrasonic signal in assessment of plastic strain in aluminum

In nonlinear ultrasonics, the correlation between microstructural change and ultrasonic properties is investigated by the acoustic nonlinearity parameter, calculated by experimentally measuring the first and second harmonic amplitudes of ultrasound signals. The most prevalent signal processing method is to transform the time-domain signal into the frequency domain and acquire the amplitudes of each frequency from the frequency spectrum. However, the major drawback of this approach is that temporal information is not preserved and the transformation errors increase dramatically in analyzing nonlinear signals with discontinuities. In this study, two wavelet-based algorithms are introduced to analyze the waveform in nonlinear ultrasonic testing. The algorithms are applied to correlate the acoustic nonlinearity parameter and the plastic deformation of aluminum 1100 specimens, for the purpose of validation. The results showed that the acoustic nonlinearity parameter calculated through the proposed algorithms is not influenced by the signal processing variables, and the signal processing error is reduced when the wavelet-based decomposition is applied. © 2017 Elsevier Ltd