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An Online Data-Driven Predictive Maintenance Approach for Railway Switches

2023; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-031-23633-4_27

1865-0937

Emanuel Sousa Tomé, Rita P. Ribeiro, Bruno Veloso, João Gama,

Power System Reliability and Maintenance

An online data-driven predictive maintenance approach for railway switches using data logs obtained from the interlocking system of the railway infrastructure is proposed in this paper. The proposed approach is detailed described and consists of a two-phase process: anomaly detection and remaining useful life prediction. The approach is applied to and validated in a real case study, the Metro do Porto, from which seven months of data is available. The approach has been revealed to be satisfactory in detecting anomalies. The results open the possibilities for further studies and validation with a more extensive dataset on the remaining useful life prediction.