Quantitative Assessment of CFRP-concrete Cylinders Using Synthetic Aperture Radar Images

Abstract

ABSTRACTA feature extraction algorithm is proposed to quantitatively assess the condition of intact and damaged carbon fiber reinforced polymer (CFRP)-wrapped concrete cylinders using synthetic aperture radar (SAR) images. The proposed algorithm converts SAR images into a simplified representation, based on the shape, size, and amplitude of SAR images. In this approach, the shape of scatterers in a SAR image is characterized by average Gaussian curvature (K), area ratio (R), and SAR amplitude (I), and is represented by a K-R-I curve. SAR images of intact and damaged CFRP-wrapped concrete cylinders were generated by a stripmap SAR imaging radar system (10.5 GHz) at various inspection angles (0°, 15°, 25°, 30°, 45°, and 60°). From our experimental result, it is found that the K-R-I representation of SAR images is capable of distinguishing damaged SAR images from intact ones at different inspection angles. Quantitative dissimilarity between the K-R-I curves of intact and damaged specimens is assessed by coefficient of correlation and compared with the signal-to-noise ratio (SNR) of SAR images. It is found that the dissimilarity of K-R-I curves is closely related to the SNR of SAR images, demonstrating the feasibility and potential of the proposed K-R-I representation.