Research on the application of YOLOv5 in station interlocking test

With the rapid development of high-speed railway, it is necessary to ensure the safety of railway running, and the computer interlock system is the key equipment to ensure the safety of railway running in the station. It is a real-time system with high safety and reliability, which needs comprehensive and strict testing before it is put into use. In order to ensure that the interlocking system can strictly complete the function of each part, the computer interlocking test is very important. In recent years, with the rapid development of deep learning and image processing technology, in order to further improve the test efficiency of computer interlocking system, this paper studies the result decision module of automatic interlocking test. Target detection algorithm YOLOv5 is adopted to realize the location and recognition of signal, switch and section icon on the interlocking interface.