Damage Progress Classification in AlSi10Mg SLM Specimens by Convolutional Neural Network and k-Fold Cross Validation.

In this study, the damage evolution stages in testing AlSi10Mg specimens manufactured using Selective Laser Melting (SLM) process are identified using Acoustic Emission (AE) technique and Convolutional Neural Network (CNN). AE signals generated during the testing of AlSi10Mg specimens are recorded and analysed to identify their time-frequency features in three different damage evolution stages: elastic stage, plastic stage, and fracture stage. Continuous Wavelet Transform (CWT) spectrograms are used for the processing of the AE signals. The AE signals from each of these stages are then used for training a CNN based on SqueezeNet. Moreover, k-fold cross validation is implemented while training the modified SqueezeNet to improve the classification efficiency of the network. The trained network shows promising results in classifying the AE signals from different damage evolution stages.

Investigation of Interlaminar Shear Properties of CFRP Composites at Elevated Temperatures Using the Lempel-Ziv Complexity of Acoustic Emission Signals.

Three-point bending tests on Short Beam Shear (SBS) specimens are performed to investigate the interlaminar shear properties of plain weave fabric CFRP composites. The tests are performed in a controlled environmental chamber at two different elevated temperatures. The interlaminar shear properties of the specimens remain largely unaffected by the testing temperature. However, the SEM micrographs show different damage progressions between the specimens tested at 100 °C and 120 °C. Fibre ruptures and longer delamination between the plies, as a result of a high temperature, are observed in the specimens tested at 120 °C, which are not observed in the specimens tested at 100 °C. In addition, the acoustic emission activities during the tests are investigated by using piezoelectric sensors. The information-theoretic parameter, the Lempel-Ziv (LZ) complexity, is calculated for the recorded acoustic signals. The LZ Complexities are used for identifying the occurrence of the first delamination failure in the specimens. Additionally, the two features of the acoustic signals, LZ complexity and Weighted Peak Frequency (W.P-Freq), are used for distinguishing the different damage sources in the CFRP specimens. The results are well-supported by the time-frequency analysis of the acoustic signals using a Continuous Wavelet Transform (CWT).