Acoustic emission based deep learning technique to predict adhesive bond strength of laser processed CFRP composites

Abstract

The high degree of inhomogeneity in material and intricacies created by machining of carbon fiber reinforced plastic (CFRP) composites hinder the accurate prediction of residual strength of the adhesive bond joint using analytical models. Recently, artificial intelligence techniques are effectively utilized as an alternative method for predicting the results of complex phenomena. In this paper, attempts were made to predict the bond strength of laser surface treated and adhesively bonded CFRP composite specimens using the artificial neural network (ANN) from the acoustic emission (AE) parameter recorded during the shear test. Twelve adhesively bonded specimens whose surfaces were pre-processed with 3W Nd:YAG laser at different processing parameters. ANN was trained using segregated AE data according to the failure mechanism and the percentage of failure load (5 to 100%). Predicted values were compared with experimental values and the results were analysed for the suitability of ANN with AE in the application.

Deep Learning Approach for Damage Classification Based on Acoustic Emission Data in Composite Materials

“…Meanwhile, with the continuous update of AE instruments, which are equipped with multi-channel and broadband sensors and real-time full waveforms which contain AEs, big data are collected. Therefore, AE technology and deep learning are linked and have been adopted by many researchers [7,[35][36][37][38][39][40][41]. The conversion of time series data into two-dimensional image data using short fast Fourier transform, wavelet transform, and the classification of acoustic emission data [42][43][44][45][46] using two-dimensional convolutional neural networks (CNNs) is a common method that has been used by many researchers.…”

Development of Thermo Mechanical Model for Prediction of Temperature Diffusion in Different FSW Tool Pin Geometries During Joining of AZ80A Mg Alloys

“…The softened & plasticized materials on both sides of the workpieces are stirred around the region of the FSW tool pin (with unique geometrical shape), by the impact of the rotational and translational movements of pin of the tool, which happens along the entire line of travel of the tool pin [14]. Once the pin of the FSW tool is retrieved from the surfaces of the flat metal plates, the plasticized material flows across the metal plates stops, then the cooling of the plasticized material takes place and the welding gets completed successfully [15][16][17].…”

An experimental study on hole quality and different delamination approaches in the drilling of CARALL, a new FML composite

“…While research on traditional carbon and glass fiber reinforced polymer (CFRP and GFRP) composites [1][2][3][4][5] and sandwich composite materials [6][7][8][9][10] is still ongoing, fiber metal laminates (FMLs) have been introduced as a new composite family in recent years in order to meet the different mechanical property demands of engineers. Fiber metal laminates are composite materials consisting of alternating layers of metal and composite bonded together using epoxy adhesive [11].…”