Research on CFRP Defects Recognition and Localization Based on Metamaterial Sensors

Abstract

In the paper, the concept of symmetry is utilized to detect internal defects in Carbon fiber reinforced polymer (CFRP), that is, the reconstruction and localization methods for internal defects in CFRP are symmetrical. CFRP is widely used in industrial, biological and other fields. When there are defects inside the composite materials, its dielectric constant, magnetic permeability, etc. change. Therefore, metamaterial sensors are widely used in non-destructive testing of CFRP Defects. This paper proposes a defect identification and location method based on principal component analysis (PCA) and support vector machine (SVM). The trained model is used to classify the dimensionally reduced data, and the reconstructed defect binary image is obtained. Simulation and physical experiment results show that the method used in this article can effectively identify and locate defects in carbon fiber composite materials.