Approaches for weigh-in-motion and wheel defect detection of railway vehicles

• Tipo: Capítulo ou Parte de Livro
• Data: 2022

Autores

Pedro Alves Costa (Autor) FEUP; Araliya Mosleh (Autor) FEUP; Pedro Aires Montenegro (Autor) FEUP; Rui Calçada (Autor) FEUP

Livro

Título: Rail Infrastructure Resilience: A Best-Practices Handbook

Páginas: 183-207

ISBN: 978-012821042-0, 978-012821043-7

Indexação

Scopus

Outras Informações

ID Authenticus: P-00X-6G6

DOI: 10.1016/b978-0-12-821042-0.00009-5

Abstract (EN): The development of efficient weigh-in-motion and wheel defect detection methods with high accuracy estimation procedures from track measurements is one of the major subjects that draw the attention of both the railway industry and scientific researchers. This information triggers a warning in the administration system when a train is overloaded or operating under abnormal conditions. The main novel aspect of this study is to define a methodology to obtain weigh the train in motion and allows the identification of a wheel flat using a wayside monitoring system. To achieve this, two approaches were proposed to obtain an estimation of the wheel static load as well as distinguish the healthy wheel from the defective one in order to allow the system to activate the necessary alerts. A wide range of numerical simulations based on a train-track interaction model has been performed for different train speeds. From the obtained results, it is evident that the proposed approaches are capable tools and cost-effective methods to estimate the wheel static load as well as an abnormal condition of rolling stock. © 2022 Elsevier Inc. All rights reserved.

Idioma: Inglês

Tipo (Avaliação Docente): Científica