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Predictive Maintenance of a Train System Using a Multilayer Perceptron Artificial Neural Network

机译:利用多层意识形人工神经网络预测维护火车系统

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Singapore has an extensive rail network and millions of people use it every day. In addition, the volume of commuters has been increasing constantly over the past 10 years which places a huge strain on the entire rail network thus stoppages in train services have become more frequent. This research is an experiment in implementing predictive maintenance on the upkeep of the trains using a multilayer perceptron artificial neural network. The steps taken to select the key parameters for condition monitoring and as inputs to the multilayer perceptron were discussed. Suitable equipment that can be used in collecting the data was also suggested. The research is currently in progress and results of the research will be published in the near future.
机译:新加坡有一个广泛的铁路网络,数百万人每天都使用它。此外,在过去的10年里,通勤者的数量在过去的10年里一直在增加,这在整个铁路网络上占据了巨大压力,因此列车服务中的停机变得更加频繁。该研究是利用多层的感知人工神经网络实施关于培训的预测维护的实验。讨论了选择条件监控的关键参数以及作为Multijayer Perceptron的输入的步骤。还提出了可用于收集数据的合适设备。该研究目前正在进行,研究结果将在不久的将来发表。

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