Fiber Bragg Grating (FBG) sensors have been increasingly used in the field of Structural Health Monitoring (SHM) in recent\nyears. In this paper, we proposed an impact localization algorithm based on the Empirical Mode Decomposition (EMD) and\nParticle Swarm Optimization-Support VectorMachine (PSO-SVM) to achieve better localization accuracy for the FBG-embedded\nplate. In our method, EMD is used to extract the features of FBG signals, and PSO-SVM is then applied to automatically train a\nclassification model for the impact localization. Meanwhile, an impact monitoring system for the FBG-embedded composites has\nbeen established to actually validate our algorithm. Moreover, the relationship between the localization accuracy and the distance\nfrom impact to the nearest sensor has also been studied. Results suggest that the localization accuracy keeps increasing and is\nsatisfactory, ranging from 93.89% to 97.14%, on our experimental conditions with the decrease of the distance. This article reports\nan effective and easy-implementing method for FBG signal processing on SHM systems of the composites.
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