Identifying the Energy of Low-velocity Impacts on Composite Components Using Acoustic Emission

Low-velocity impacts (LVI) caused by debris and hail can be one of the main threats to the integrity of aircraft components. Identifying the energy levels of LVI is critical to assessing the damage caused by the impacts on the aircraft. The traditional approach to identifying the energy of impacts is the C-Scan using the ultrasonic technique. However, this assessment cannot be used in real-time and is only available between flight missions. Moreover, the C-Scans are performed manually and can be affected by human errors. However, thanks to recent advances in sensing technology, structural health monitoring methods such as acoustic emission monitoring can now be applied to composite impact assessment. The innovation of this paper lies in the development of an impact energy assessment system using one acoustic emission sensor. In this system, a deep convolutional neural network was used to identify the impact energies and classify the impacts into five levels. The results demonstrate the effectiveness and potential of the proposed framework.