An Online Data-Driven Predictive Maintenance Approach for Railway Switches

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2023

Autores

Tome, ES (Autor) Outra; Rita Ribeiro (Autor) FCUP; Veloso, B (Autor) FEP; João Gama (Autor) FEP

Ata de Conferência Internacional

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

Páginas: 410-422

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

Grenoble, FRANCE, SEP 19-23, 2022

Indexação

ISI Web of Knowledge - 2 Citações

Scopus - 2 Citações

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 13