Experimental Cost Reduction for Delamination Monitoring of CFRP Beam Using Electrical Resistance Change with Neural Networks(International Workshop on Smart Materials and Structural Systems, W03 Jointly organized by Material & Processing Division, Materia

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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 fibres as sensors. In our previous paper, an actual delamination crack in a Carbon Fiber Reinforced Plastics (CFRP) laminate was experimentally identified with artificial nerura networks (ANN) or response surfaces created froma large number of experiments. The experimental results were used for the learning of the ANN or for regressions of the respons surfaces. For the actual application of the method, it is necessary to minimヌze the number of experiments in order to keep the cost of the experiments to a minimum. In the present study, therefore, FEM analyses are employed to make sets of data for the learning of the ANN. Firstly, the electrical conductivity of the CFRP laminate is identified by means of the least estimation error method. After that, the results of the FEM analyses are used for the learning of the ANN. The method is applied to the actual delamination monitoring of CFRP beams. As a result, the method successfully monitored the delamination location and size using only ten experiments.
一般社団法人日本機械学会の論文
2004-09-04