Abstract: Honeycomb sandwiched structures are widely used in aerospace field, but during service it is inevitable for them to encounter damage, especially impact damage that can significantly reduce their strength. Combined with modern electronic printing technology, this study directly fabricates intelligent sensing layers on the surface of honeycomb sandwiched structure with conductive graphene-doped carbon ink and silver ink through screen printing, and identifies low-velocity impact damage with electrical tomography. Drop-weight device is used to impact the structure with low velocity, and the boundary voltage change of the sensing layer before and after impact is gathered by the electrical test system through injecting a tiny current into it. By analyzing the voltage data, sparse regularization algorithm, SpaRSA, is employed to reconstruct the image of conductivity change of the sensing layer to visualize damage information. Experimental results have demonstrated that, the proposed method can effectively identify the number, locations and approximate sizes of impact damage. And compared with traditional Tikhonov regularization-based algorithm, the sparse tomography algorithm can achieve better identification accuracy for damage sizes, providing a novel way of online impact damage identification for honeycomb sandwiched structures.

Key words: honeycomb sandwich structure, impact damage identification, printed sensing layer, electrical tomography, sparse regularization algorithm, composites