Abstract
In this paper, an in-situ damage detection framework for carbon fiber-reinforced plastics (CFRPs) is proposed. The methodology involves the design of an electromagnetic tomography (EMT) sensor and developing an absolute image reconstruction method for electromagnetic tomography. A linear EMT sensor is designed for in-situ structural health monitoring of CFRPs tensile load test specimens. A compatible multi-template supervised descent method (cmt-SDM) based on a normal mixture distribution model of pixels is proposed for EMT image reconstruction. The cmt-SDM was developed to overcome the ill-posed problem in absolute image reconstruction. Simulation and experimental results show that the method proposed in this paper can be employed to monitor and evaluate the local damage degree of CFRPs specimens under quasi-static tensile loading. In addition, when the local fiber-breaking ratio reaches 40%, the damage location can be accurately reflected by the imaging results. Compared with the traditional SDM method, the method proposed in this paper shows smaller estimation error and delivers more accurate reconstructed images.
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