采用人工智能的方法,对车站信号联锁系统故障诊断系统的开发与实现方法进行分析和探讨.根据车站信号设备复杂的结构特点,建立一种分层多级信息融合的故障诊断方法.首先针对来自各子系统的状态信息,应用故障树系统进行分层分级判断:然后,将子系统诊断结果应用D-S证据理论加以综合,给出信号设备的故障诊断决策.通过评怙证据的可靠性,降低识别的整体误差,提高诊断的准确性.
Development and implementation of the station signaling interlocking system fault diagnosis system are studied by the artificial intelligence system methods. According to the station signaling structural characteristic with complex equipment, a fault diagnosing method based on hierarchical information fusion is presented. In this method, Firstly fault tree expert system is applied to field fault multiple hierarchical diagnosis judgment on the basis of state information from subsystems, then D - S evidence theory is used to synthesis the diagnosis results from subsystems and give the signaling equipment diagnosing decision.This method can be used to evaluate the reliability of evidence, reduce the overall error of recognition frame, and raise the accuracy of fault diagnosis.