摘要
地铁车辆的客室车门因数量多、开关频繁,是列车的主要故障系统之一,一旦正线发生车门故障,极易造成晚点。基于广州地铁某线路的现有车门故障数据,提出将灰色GM(1,1)模型与马尔可夫链相结合,对车门系统的年故障次数作出预测。结果表明灰色GM(1,1)模型表示出了故障的总体发展趋势,灰色马尔可夫模型则很准确地预测了车门系统的年故障次数。对预测值的进一步延展,可以得到车门系统在维持现有检修模式下未来的年故障次数,用预测结果指导未来的检修维护策略,适当更新定期维护频率,可提高车门系统的可靠性。
The passenger compartment door is one of the most fault system of the subway vehicle, because the door work frequently. Once the door is fault, easily causing the delay. Based on the fault data of passenger com- partment door from guangzhou metro, the paper introduces the grey GM （ 1,1 ） model and the markov chain to pre- dict the fault data for passenger compartment doors. The results show that the grey GM （ 1,1 ） model is the overall development trend of the fault, the Grey-Markov model is more accurate to predict the fault data for the door sys- tem. The further extend of the predict value can get the door system in the maintenance of the existing mode. With the forecast results, we can improve the reliability of the door system.
出处
《装备制造技术》
2017年第3期223-226,共4页
Equipment Manufacturing Technology
关键词
客室车门故障
随机振荡序列
灰色GM(1
1)模型
马尔可夫链
the fault of passenger compartment door
random oscillation sequence
grey GM （1,1） model
markov chain
