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1、附录A外文资料 Development of Railway Station Signaling Control Equipment Fault Diagnosis Expert System Abstract Development and implementation of the station signaling control equipment fault diagnosis expert system are studied by the artificial intelligence and expert system methods. On the basis of the
2、current situation of station signaling computer monitoring system, the overall structure of the station signaling equipment fault diagnosis expert system is proposed, which consists of the knowledge base subsystem, machine reasoning subsystem, integrated database subsystem and man-machine interfacin
3、g subsystem. According to the types and characteristics of faults are established the fault mechanism analysis model based on the principle of logic circuits, the fault analysis model based on actual expert knowledge, the fault diagnosis & trend analysis model based on the equipment life mechanism a
4、nd the complex fault diagnosis model based on the decision tree learning algorithm. The prototype system is developed with the object-oriented structural knowledge representation methods and the element classification development technology, thus laying a foundation for development of the practical
5、application system. Research and development to ensure the safety of railway transport station signal equipment maintenance system . To ensure trouble-free railway station signal equipment in good work, is our country railway currently facing a major issue. To improve the maintenance level of railwa
6、y signal system in our country, starting in the 90 s, has developed the TJ WX - type I and TJ WX - 2000 type microcomputer monitoring system. Since 2000, most of the electric centralized station by using the computer monitoring system, realize the real-time monitoring for station signal equipment st
7、atus ，has been basically achieve the goal of a modern sensor technology, field bus, computer network communication, database and software engineering, And through the main signal monitoring and recording equipment running status, grasp the current state of the equipment for electricity department an
8、d accident analysis provides the basic scientific basis. But as a result of the system and there is no perfect condition monitoring and fault diagnosis in a bodys comprehensive function, makes a lot of complicated equipment failure and driving, and analyzing the cause of the accident still need to r
9、ely on artificial experience. So only on the existing computer monitoring system, can not meet modern electricity implement status maintenance management of the overall goal of a black box. To this end, the ministry of railways in 2004 put forward the research and development railway station signal
10、equipment fault diagnosis expert system project. Focus on the overall structure of the fault diagnosis expert system design, the main model and the method of fault diagnosis, and the prototype of the system implementation content such as software development were studied. The project through to the
11、railway station signal equipment failure mechanism analysis, the corresponding fault diagnosis model is established and the method, and by using expert system theory and method to develop the corresponding fault diagnosis intelligent analysis application software system. A: The overall structure of
12、the expert system for railway station signal equipment failure Because of the complexity of the railway station signal system equipment failure, according to the basic composition principle of expert system, the design of the railway station signal equipment fault diagnosis expert system of general
13、structure, as shown. This expert system is mainly composed of knowledge acquisition subsystem, equipment condition monitoring data import, subsystems of knowledge base, reasoning machine system, integrated database and function modules such as human-computer interaction interface subsystem. 1.1Knowl
14、edge acquisition subsystem function module The main module of empirical knowledge and professional knowledge in the field of acquisition, analysis and processing, and other functions, to provide knowledge base of expert system diagnosis knowledge and rules. Knowledge acquisition process can be compl
15、eted by artificial directly, also can indirectly through some knowledge acquisition method. This article USES the method of fault diagnosis knowledge acquisition mainly includes: based on the principle of the circuit model and the logic of the failure mechanism of knowledge acquisition method, based
16、 on the experience of the maintenance personnel fault handling the actual method of knowledge acquisition, knowledge acquisition method based on the mechanism of equipment life, as well as self-learning knowledge acquisition method based on the examples of statistical information, etc. 1.2 The equipment condition monitoring data import function module The main module from the railway station signal microcomputer monitoring s
