The RFID Electronic Tag Defect Detection System Based On YOLOv5 For Industrial Scenarios

Abstract

Recent technological progress has promoted a large number of development trends in the Radio Frequency Identification (RFID) system. RFID tag detection/identification is one of the most critical problems in successfully deploying the RFID system in various applications. However, many significant issues related to detecting RFID tag defects have not been addressed. The main problems of RFID electronic tag defect detection methods in industrial scenarios are low efficiency, low accuracy, and high labor costs. This paper analyses the characteristics of RFID tag defects based on defect samples, and a detection and prediction method related to YOLOv5 is proposed. In this experiment, a real-time RFID tag defect intelligent detection system embedded in the YOLOv5 model was developed and applied to industrial production. The results show that this system has higher accuracy in defect detection, faster detection time, and saves labor costs, which can meet industrial needs.