Impact Area Estimation in CFRP Panels by Cross-Correlation Driven Features and Distributed Sensing

Abstract

In this paper, the identification of impact area that works only with the readout responses opportunely post processed, is proposed. The readouts signal is representative of a distributed high resolution strain map under backscattering random noise and static excitation. The algorithm is based on first order derivative operator already developed by the author. Up to four features are extracted from time and spatial domain. Then the cross-correlation function is applied to improve signal to noise ratio. A basic triangle cluster applying the Delaunay algorithm for area reconstruction is implemented. The methodology is applied to estimate the surface extension of an impact damage induced by low/medium energy impacts on 24 and 36 ply CFRP panels with non-unidirectional layups. The results show a good coherence with respect to the ultrasonic NDI controls.