Matteo Vagnoli
Towards a real-time Structural Health Monitoring of railway bridges
Vagnoli, Matteo; Remenyte-Prescott, Rasa; Andrews, John
Authors
Dr RASA REMENYTE-PRESCOTT R.REMENYTE-PRESCOTT@NOTTINGHAM.AC.UK
ASSOCIATE PROFESSOR
Professor JOHN ANDREWS john.andrews@nottingham.ac.uk
PROFESSOR OF INFRASTRUCTURE ASSET MANAGEMENT
Abstract
More than 350,000 railway bridges are present on the European railway network, making them a key infrastructure of the whole railway network. Railway bridges are continuously exposed to changing environmental threats, such as wind, floods and traffic load, which can affect safety and reliability of the bridge. Furthermore, a problem on a bridge can affect the whole railway network by increasing the vulnerability of the geographic area, served by the railway network. In this paper a Bayesian Belief Network (BBN) method is presented in order to move from visual inspection towards a real time Structural Health Monitoring (SHM) of the bridge. It is proposed that the health state of a steel truss bridge is continuously monitored by taking account of the health state of each bridge element. In this way, levels of bridge deterioration can be identified before they become critical, the risk of direct and indirect economic losses can be reduced by defining optimal bridge maintenance works, and the reliability of the bridge can be improved by identifying possible hidden vulnerabilities among different bridge elements.
Citation
Vagnoli, M., Remenyte-Prescott, R., & Andrews, J. Towards a real-time Structural Health Monitoring of railway bridges. Presented at 52nd ESReDA Seminar on Critical Infrastructures Enhancing Preparedness & Resilience for the security of citizens and services supply continuity
Conference Name | 52nd ESReDA Seminar on Critical Infrastructures Enhancing Preparedness & Resilience for the security of citizens and services supply continuity. |
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End Date | May 31, 2017 |
Acceptance Date | Mar 8, 2017 |
Publication Date | May 31, 2017 |
Deposit Date | Oct 2, 2017 |
Publicly Available Date | Oct 2, 2017 |
Peer Reviewed | Peer Reviewed |
Keywords | Real-time monitoring; Structural Health Monitoring; Bayesian Belief Networks; Steel truss bridge |
Public URL | https://nottingham-repository.worktribe.com/output/863951 |
Related Public URLs | https://www.eurosafe-forum.org/node/366 |
Contract Date | Oct 2, 2017 |
Files
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