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首页> 外文会议>Proceedings of the 3rd international conference on electrical and information technologies for rail transportation: transportation >A Bayesian-MCMC Model to Assess Metro Train Collector Shoes Slider Degradation Under Different Materials
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A Bayesian-MCMC Model to Assess Metro Train Collector Shoes Slider Degradation Under Different Materials

机译：贝叶斯-MCMC模型评估不同材料下地铁列车集线器滑块滑移性能

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摘要

This paper presents a Bayesian-MCMC model to assess collector shoes slider degradation under different materials. A Markov Chain Monte Carlo (MCMC) method, based on the Bayesian decision model, is put forward and built up a framework in case of the life cycle of collector shoes under different materials forecast. All of inspection data is gathered from Beijing metro lines, and WinBUGS software are used to predict the slider's wear rate. Result shows that the difference between the predicted value and the real one is less than 10% of the later one. Consequently, in case of new metro equipment parts, the newest method is able to ensure the safety operation in the metro by providing a valid device to the equipment manufacturers, the maintenance department as well as the purchasing department of the metro equipment.
机译：本文提出了一种贝叶斯-MCMC模型，以评估不同材料下集电靴滑块的退化。提出了一种基于贝叶斯决策模型的马尔可夫链蒙特卡洛（MCMC）方法，并建立了在不同材料预测条件下集热靴寿命周期的框架。所有的检查数据都是从北京地铁收集的，WinBUGS软件用于预测滑块的磨损率。结果表明，预测值与实际值之差小于后一个值的10％。因此，在新的地铁设备零件的情况下，最新的方法能够通过向地铁设备的设备制造商，维护部门以及采购部门提供有效的设备来确保地铁的安全运行。

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