Drive-by Methodologies Applied to Railway Infrastructure Subsystems: A Literature Review-Part II: Track and Vehicle

Author(s)

Braganca, Cassio ; Souza, Edson F. ; Ribeiro, Diogo ; Meixedo, Andreia ; Bittencourt, Tulio N. ; Carvalho, Hermes

• Document type: Journal article
• Source: APPLIED SCIENCES-BASEL; v. 13, n. 12, p. 29-pg., 2023-06-01.

Abstract

Railways are one of the most important means of transportation, allowing people and goods to move quickly, environmentally beneficially, and efficiently over long distances. To ensure safe and reliable operations, regular condition-based assessments of trains and track are of paramount importance. Drive-by methodologies, which utilize data collected by onboard monitoring systems as the vehicle travels over the track, have gained popularity as an economically viable strategy for monitoring extensive track networks as well as vehicles traveling on them. This paper presents a critical review of these methodologies applied to railway tracks and vehicles. It assesses research on track irregularities, rail conditions, and the condition of rail supporting elements, highlighting important early developments and recent papers that provide insights into future practical applications. Additionally, the paper explores works related to global vehicle condition evaluation, focusing on the identification of suspension and wheelset element damage and also discussing challenges towards commercial application. The findings suggest that drive-by methodologies have several promising future applications. These include track maintenance optimization, proactive fault detection, predictive maintenance, track performance evaluation, vehicle health monitoring, and data-driven decision-making. By leveraging drive-by assessments, railway operators can optimize maintenance efforts, detect faults early, predict remaining component life, evaluate track performance, monitor vehicle health, and make informed decisions based on data analysis. Finally, a comprehensive conclusion summarizes the achievements thus far and provides perspectives for forthcoming developments. The future practical applications of drive-by methodologies discussed in this review have the potential to revolutionize railway track and vehicle assessments, leading to safer and more efficient railway operations in the days to come. (AU)

• FAPESP's process: 22/13045-1 - Development of methodologies for damage identification in railway bridges based on indirect monitoring and machine learning algorithms
• Grantee: Cassio Scarpelli Cabral de Braganca
• Support Opportunities: Scholarships in Brazil - Doctorate