Development of high-speed railway signal testing technology and its application in system safety assessment

With the rapid development of high-speed railway technology, the complexity and accuracy of signal system are constantly improving, which puts forward higher requirements for signal testing technology. As a key link to ensure the normal operation of high-speed railway signal system, signal testing technology has experienced the evolution from basic manual testing to highly automated and intelligent testing. In the early stage, high-speed railway signal testing mainly relies on manual operation and simple equipment, and the performance is evaluated by field observation and recording data. Subsequently, with the development of technology, the automatic test system came into being, which significantly improved the efficiency and accuracy of the test, simulated the operation of the signal system in various scenarios, and helped engineers quickly locate and solve potential problems. In recent years, with the help of AI and big data technology, the emergence of intelligent test system has realized the automatic identification and optimization suggestion of abnormal situation of signal system, which has provided strong support for the continuous improvement of the system. High-speed railway signal testing technology plays a vital role in system safety assessment. This technology can not only detect system faults, but also verify the function and performance of the system to ensure the safety and reliability of the whole signal system. Taking the CTCS-3 train control system as an example, the signal testing technology based on simulation testing has conducted a comprehensive safety assessment of the train control system by constructing a virtual test environment and simulating the real train operation scene, which provides a strong guarantee for the safe operation of high-speed railways. However, the signal testing technology also has limitations in system security assessment, such as technical dependence, scene limitation, cost issues and update challenges. In order to further improve its application effect, this paper suggests strengthening technical training, increasing real scene simulation, optimizing test cost, continuously updating technology and introducing intelligent technology.