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

机译:使用多层感知器人工神经网络的火车系统的预测维护

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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:新加坡拥有广泛的铁路网络,每天都有数百万人使用。另外,在过去的十年中,通勤者的数量一直在不断增加,这给整个铁路网络带来了巨大的压力,因此火车服务的停站变得更加频繁。这项研究是使用多层感知器人工神经网络对火车进行保养维护的实验。讨论了选择关键参数进行状态监测以及作为多层感知器输入的步骤。还建议了可用于收集数据的合适设备。研究正在进行中,研究结果将在不久的将来发布。

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