抄録
The present study employs an electric resistance change method for identifications of delamination cracks. For the method, diagnostic tools for the inverse problems to identify the delamination crack location and size from the electric resistance changes are discussed. FEM analyses are conducted to obtain electric resistance changes due to delamination crack creations with fiveelectrode type specimens. By comparisons of the estimations with the Artificial Neural Networks (ANNs) and with the response surfaces (RS), a better diagnostic tool is discussed in detail. As a result, because of overlearning of neural network, the presumed error of new data with ANNs is large, and the RS using quadratic polynomials is a better tool than ANNs for identifications of delamination crack location and size using electric resistance change.
