基于模式匹配算法的机车信号故障诊断的研究

The Study of Cab Signal Fault Diagnosis Based on Pattern Matching Algorithm

机车信号的码序提供了机车信号是否发生故障和发生何种故障的信息。本文分析了机车信号的故障码序,通过总结其规律与特点,将机车信号的故障诊断问题归类为模式匹配问题。并在此基础上将模式匹配问题与机车信号的故障诊断问题相结合,提出了基于多模式匹配算法DFSA(Deterministic Finite State Automata)的机车信号故障诊断模型。该模型通过建立转向(goto)函数、失效(failure)函数和输出(output)函数,利用树型有限自动机实现了对机车信号快速准确的故障诊断。通过对实际的机车信号检测记录仪记录的数据进行故障诊断实验,表明该模型在机车信号故障诊断中的有效性。

Cab signal code sequences provide the information about wether any cab signal fault happens or not and what categories the cab signal fault belongs to. This paper analyzes the code sequence of fault cab signals in respect of its rule and characteristics. The problem of cab signal fault diagnosis is classified as the pattern matching problem. The cab signal fault diagnosis problem is combined with the pattern matching problem on the basis of this conclusion. A cab signal fault diagnosis model based on Multiple Patterns Matching Algorithm DFSA （Deterministic Finite State Automata） is proposed. The Goto function, failure function and output function are established and the model achieves fast and exact fault diagnosis by using dendriform finite state automata. The fault diagnosis experiment with the actual data collected from the cab signal detector shows that the model is effective in cab signal fault diagnosis.