Abstract
The Railroad Switch denotes a set of parts in concordance with two lines in order to allow the passage of railway vehicles from one line to another. The Switch Machines are equipments used for handling Railroad Switches. Among all possible defects that can occur in a electromechanical Switch Machine, this work emphasizes the three main ones: the defect related to lack of lubrication, the defect related to lack of adjustment and the defect related to some component of Switch Machine. In addition, this work includes the normal operation of these equipments. The proposal in question makes use of real data provided by a company of the railway sector. Observing these four events, it is proposed the use of Signal Processing and Computational Intelligence techniques to classify the mentioned events, generating benefits that will be discussed and thus providing solutions for the company to reach the top of operational excellence.
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Aguiar, E. et al. (2014). Classification of Events in Switch Machines Using Bayes, Fuzzy Logic System and Neural Network. In: Mladenov, V., Jayne, C., Iliadis, L. (eds) Engineering Applications of Neural Networks. EANN 2014. Communications in Computer and Information Science, vol 459. Springer, Cham. https://doi.org/10.1007/978-3-319-11071-4_8
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DOI: https://doi.org/10.1007/978-3-319-11071-4_8
Publisher Name: Springer, Cham
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