Application And Research On Artificial Intelligence Techniques In Fault Diagnosis In Railway Station Signal

Interlocking control system of signaling at railway stations is a key equipment which ensures the traveling safety and improves the traveling efficiency. Electrical centralization interlocking system, which is generally adopted, has some disadvantages, such as huge maintenance of equipment and lower reliability. When failure has been happened in the implement, it cannot suit the accelerating demand in nowadays that depends on manual methods to detect the failure. Thus, based on signaling equipments' working theory and characteristic of failure, adopting the method of experts system, the failing equipments can be diagnosed and settled. It is also provide scientific decisions. This method has critical significance to ensure traveling safety and advance traveling efficiency.On the background of research and application of interlocking system, this thesis researches on the detecting failures of interlocking system. It has done the jobs as following:1. Based on extensive consulting correlative information, the summarizing of detecting failure technology has been made. In addition, we advance the significance and importance of experts system of detecting failure in railway stations.2. On the basic of existent structure of experts system, we design the structure and key technology of experts system in railway stations.3. After researching the working and failing theory of relay electrical centralization interlocking system, we design the knowledge base of core department and realizing method of reasoning machine in expert system of detecting failure.4. Subsystem modules were realized to detect failures, which were made by the environment of Visual C++. Through such measure, it was tested and validated about the system.Through analyzing and testing, experts system of this thesis can effectively detect failure for failures of interlocking system. It also validates the system can availably work.