Classification of de-bond in multi-layered steel-rubber adhesive structure with character of DCT spectra by artificial neural networks

The character of bond defects in the multi-layered steel-rubber adhesive structure was studied by DCT. Using artificial neural networks, the de-bond at interface Ⅰ, Ⅱ,Ⅲ and Ⅳ was classified. The result show that the features extracted by our algorithms is good pattern for recognition. This enable automatic detection and recognition of de-bond in industry application.