An Online Data-Driven Predictive Maintenance Approach for Railway Switches

• Type: Article in International Conference Proceedings Book
• Date: 2023

Authors

Tome, ES (Author) Other; Rita Ribeiro (Author) FCUP; Veloso, B (Author) FEP; João Gama (Author) FEP

Conference proceedings International

Title: MACHINE LEARNING AND PRINCIPLES AND PRACTICE OF KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2022, PT II

Pages: 410-422

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)

Grenoble, FRANCE, SEP 19-23, 2022

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

Other information

Authenticus ID: P-00X-T4Q

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

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13