Multiresonance Chipless RFID Sensor Tag for Metal Defect Characterization Using Principal Component Analysis

Abstract

One of the challenges in structural health monitoring (SHM) is that defects, such as metal cracks and corrosions, can occur with multiple material properties and multilayer structure, entangled with influences from the reader system and the environment. This paper presents a multiresonance chipless radio frequency identification (RFID) sensor tag and the chipless RFID sensor reader applying principal component analysis (PCA) for multiparameter estimation in metal defect characterization. The proposed sensor tag is composed of the crossed diagonal dipole patches and the L-shaped patches generating six resonance peaks within 2-6-GHz band. The frequency signature of the sensor tag is acquired and processed by a chipless RFID reader implemented using an ultra-wideband impulse radar (UWB-IR) transceiver module. We demonstrate that the multiresonance chipless RFID sensor tag in conjunction with PCA-based feature extraction and selection can be applied for the characterization of metal crack with different widths and orientations. Furthermore, the proposed technique can find a robust feature indicating corrosion stages under a coating layer regardless of the sample orientation. This paper paves the way for multiparameter defect sensing and monitoring using a chipless RFID sensor system.