Design and implementation of urban rail transit equipment board indicators detection system based on image recognition technology

Urban rail transit train signal system is crucial for ensuring the safe operation of railways. To address this issue, an urban rail transit equipment board Light Emitting Diode (LED) indicators detection system based on image recognition technology is proposed. This study realizes the status and color recognition of equipment board LED indicators based on the You Only Look Once (YOLO) architecture. After training and analyzing the algorithm model, the detection system can efficiently and accurately detect equipment LED indicators while ensuring fast processing speed. The results demonstrate that the urban rail transit equipment LED indicators detection system is highly efficient and has a low omission rate. It significantly reduces the costs associated with manual inspections and substantially improves the intelligent Operations and Maintenance (O&M) capabilities of urban rail transit equipment.