铁路信号非线性系统故障诊断方法研究

基于二值逻辑的故障诊断方法将系统状态分为正常状态和故障状态。本文针对介于正常状态和故障状态之间的中间状态,提出一种基于模糊逻辑和粒子滤波的非线性系统故障诊断方法。模糊逻辑可以描述非线性系统的故障渐变过程,而粒子滤波可以评估系统状态。通过比较不同故障等级的实际系统状态与系统评估状态,所得到的残差可作为故障诊断标准。以某型铁路信号控制系统的非线性系统为研究对象,利用不同开关状态模拟各种系统故障,仿真结果表明:该方法比传统二值逻辑故障诊断方法的精度更高,且诊断结果能够体现系统故障等级,较准确地反映系统实际故障情况,可以提高信号系统故障诊断的准确性。

Research on Fault Diagnosis Method of Nonlinear Railway Signaling Systems

The fault diagnosis method based on two-valued logic divides system states into two categories:normal state and fault state.Focusing on the transition states between the normal state and the fault state,a fault diagnosis method based on fuzzy logic and particle filter for nonlinear systems is proposed.Hereinto,fuzzy logic can describe the gradual process of fault transformation of a non-linear system and particle filter can be used to estimate the system's states.By comparing the estimated states with the actual system states at different fault levels,the resulting residual is selected as the diagnosis criterion.The nonlinear system of a railway signal control system is studied and the different switch states are used to simulate possible system faults.The simulation results indicate that the proposed method can achieve more accuracy than traditional two-valued logic fault diagnose method and indicate the grade of system faults.Hence,this method can reflect the real faults of the system and improve the accuracy of fault diagnosis of the signal system.