Nondestructive Diagnostic Measurement Methods for HF RFID Devices With AI Assistance

Abstract

This article presents different methods for noninvasive validation and diagnostics of contactless devices. The radio frequency systems studied here operate at 13.56 MHz. When manufacturing these systems in volume, it is essential to separate the fully functional devices from the totally defective ones or even from those communicating but have anomalies that will lead to a significant reduction of their lifetime. This article compares two noninvasive methods, one based on impedance measurements and the other on impulse response measurements. The advantages and drawbacks of these methods are presented and compared to their use in large-scale manufacturing. In addition to the proposed methods, this article describes two decision-making methodologies based on machine learning. This article compares also both measurement methods and machine learning tools. A robustness study shows the limitations of the employed techniques

Keywords

• Density-based spatial clustering of applications with noise (DBSCAN)
• impedance measurement
• impulse response
• machine learning
• near-field communication (NFC)
• neural network