铁路超限货物自动检测技术应用综述OA

Railway out-of-gauge cargo transportation features great difficulty and imposes strict requirements on the professional competence of railway staff and the relevant infrastructure.Based on railway out-of-gauge cargo classification standards,this paper sorted out dimension measurement methods and out-of-gauge level judgment modes and focused on analyzing the application status and effects of automatic detection technologies,namely binocular stereo vision,infrared and high-speed camera imaging,and Faster R-CNN deep learning.However,the railway out-of-gauge detection field still faces prominent challenges:low automation popularization rate,as well as insufficient positioning stability and complex environment adaptability of existing auxiliary detection technologies.Therefore,relevant technologies require in-depth research.As a result,an AI-based automatic detection technical path was proposed to achieve real-time out-of-gauge cargo identification,providing technical support for the safe and stable operation of railway freight transportation.