In this study, the carbon fiber reinforced plastics (CFRP) specimens bonded adhesively in joggled lap configuration are tested for their bonding characteristics. The acoustic emission (AE) technique is used as a characterizing tool and peak amplitude is taken as the primary acoustic descriptor. The peak amplitude distributed in the time domain of the test is clustered by using an unsupervised pattern recognition algorithm (k-means++ algorithm) to differentiate the different damage modes. Furthermore, the waveforms of the acoustic signals recorded were studied using wavelet packet transform (WPT). The frequency band associated with each damage mode is identified using the wavelet packet transform. It is identified that the dominant damage mode responsible for failure is the interfacial debonding and interlaminar crack growth through the thickness of the adhesive layer. Overall, the acoustic emission technique proved to be a powerful tool in evaluating the bonding characteristics of the tested CFRP joggled lap specimens.
Evaluating Bonding Characteristics of Joggled Lap CFRP Using Acoustic Emission Techniques / Barile, Claudia; Casavola, Caterina; Pappalettera, Giovanni; Pappalettere, Carmine; Paramsamy Nadar Kannan, Vimalathithan (STRUCTURAL INTEGRITY). - In: Proceedings of the Third International Conference on Theoretical, Applied and Experimental Mechanics / [a cura di] Emmanuel Gdoutos; Maria Konsta-Gdoutos. - STAMPA. - Cham, CH : Springer, 2020. - ISBN 978-3-030-47882-7. - pp. 26-31 [10.1007/978-3-030-47883-4_5]
Evaluating Bonding Characteristics of Joggled Lap CFRP Using Acoustic Emission Techniques
Claudia Barile
;Caterina Casavola;Giovanni Pappalettera;Paramsamy Kannan Vimalathithan
2020
Abstract
In this study, the carbon fiber reinforced plastics (CFRP) specimens bonded adhesively in joggled lap configuration are tested for their bonding characteristics. The acoustic emission (AE) technique is used as a characterizing tool and peak amplitude is taken as the primary acoustic descriptor. The peak amplitude distributed in the time domain of the test is clustered by using an unsupervised pattern recognition algorithm (k-means++ algorithm) to differentiate the different damage modes. Furthermore, the waveforms of the acoustic signals recorded were studied using wavelet packet transform (WPT). The frequency band associated with each damage mode is identified using the wavelet packet transform. It is identified that the dominant damage mode responsible for failure is the interfacial debonding and interlaminar crack growth through the thickness of the adhesive layer. Overall, the acoustic emission technique proved to be a powerful tool in evaluating the bonding characteristics of the tested CFRP joggled lap specimens.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
