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

Abstract

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.