Drive-by Methodologies Applied to Railway Infrastructure Subsystems: A Literature Review-Part I: Bridges and Viaducts

Author(s)

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

• Document type: Journal article
• Source: APPLIED SCIENCES-BASEL; v. 13, n. 12, p. 31-pg., 2023-06-01.

Abstract

Bridges and viaducts are critical components of railway transport infrastructures, providing safe and efficient means for trains to cross over natural barriers such as rivers and valleys. Ensuring the continuous safe operation of these structures is therefore essential to avoid disastrous economic consequences and even human losses. Drive-by methodologies have emerged as a potential and cost-effective monitoring solution for accurately and prematurely detecting damage based on instrumented vehicles while minimizing disruptions to train operations. This paper presents a critical review of drive-by methodologies applied to bridges and viaducts. Firstly, the premises of the method are briefly reviewed, and the potential applications are discussed. In sequence, several works involving the use of drive-by methodologies for modal characteristic extraction are presented, encompassing the most important methodologies developed over time as well as recent advancements in the field. Finally, the problem of damage identification is discussed-both in relation to modal and non-modal parameter-based techniques considering the most promising features and the current advancements in the development of methodologies for damage detection based on machine learning algorithms. A comprehensive conclusion is presented at the end of the article, summarizing the achievements and providing perspectives for future developments. By critically assessing the application of drive-by methodologies to bridges and viaducts, this paper contributes to the advancement of knowledge in this crucial area, emphasizing the significance of continuous monitoring for ensuring the integrity and safety of these vital transport infrastructures. (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