Cost-reduction method for delamination monitoring using electrical resistance changes of CFRP beam

摘要

Delamination is a significant defect of laminated composites. The present study employs an electrical resistance change method in an attempt to identify internal delaminations experimentally. The method adopts reinforcing carbon fibers as sensors. In our previous paper, an actual delamination crack in a Carbon Fiber Reinforced Plastics (CFRP) laminate was experimentally identified with artificial neural networks (ANN) or response surfaces created from a large number of experiments. The experimental results were used for learning of the ANN or regression of the response surfaces. For the actual application of the method, it is indispensable to reduce the number of experiments to suppress the total experimental cost. In the present study, therefore, FEM analyses are employed to make sets of data for learning of the ANN. First, electrical conductivity of the CFRP laminate is identified by means of the least estimation error method. After that, the results of FEM analyses are used for learning of the ANN. The method is applied to actual delamination monitoring of CFRP beams. As a result, the method successfully monitored the delamination location and size only with ten experiments.