模糊贝叶斯决策在ATP车载设备故障诊断中的应用研究

高速列车长时间工作运行不可避免发生故障,其中的车载设备故障发生具有不确定性和相关性特性。分析故障发生和查找故障致因是一项复杂而重要的过程和工作。贝叶斯网络在解决不确定性和相关性问题有其独特的优势,可以利用贝叶斯网络查找故障成因和故障点并且加以控制,从而提高列控车载设备运行的安全性。在实际理论和工程实践中运用贝叶斯推理时往往过分强调贝叶斯推理功能而忽略先验概率确定的问题,模糊贝叶斯决策是在经典贝叶斯理论上综合运用决策理论、模糊数学、贝叶斯方法和期望效用理论,建立一个在多属性指标下故障态势的模糊贝叶斯决策模型,克服了单一贝叶斯推理的不足,增强了模型的适用性。

Apply Fuzzy Bayesian Decision-making to ATP on-board Equipment Fault Diagnosis

Long time operation of the high-speed train is likely to encounter some failures,and the failures of on-board equipment are of uncertainty and correlated. Analysis of the failures and there causes is a complicated and important process. Bayesian network has unique advantages to deal with the uncertainty and correlation. Bayesian network can be used to look for and control failure causes and failure points to improve the safety of train operations. The practical theory of and engineering practice in using Bayesian for inference often put too much emphasis on functions of Bayesian inference and ignore the prior probability. Fuzzy Bayesian decision-making is based on classical Bayesian theory integrates the use of decision theory,fuzzy mathematics,the Bayesian method and expected utility theory to establish a fuzzy Bayesian decision- making model with fault situation under multiple attribute index, which overcomes the deficiency of the single Bayesian inference,and enhances the applicability of the model.