Statistical Analysis of Bridge Management System Inspection Data Conferences

abstract

• <p>Bridge inspection is essential for sustaining safe and well-performing transportation networks. The Ministry of Transportation of Ontario (MTO) bi-yearly inspects over 2800 bridges in Ontario, Canada. Then assigns each bridge a Bridge Condition Index (BCI) representing its performance level and required rehabilitation<span>.</span>As this is a time and resources consuming practice, this study explores the BCI trends which can allow a better control on inspection and maintenance scheduling. First, statistical analysis is conducted to identify the correlation of the bridge parameters with the BCI. The analysis reveals that the main parameters associated with BCI are bridge age, and time since last major and minor maintenances. Then, multivariate regression analysis is performed to establish a BCI prediction equation function of these parameters. The proposed framework can supplement existing practices for smarter inspection and maintenance scheduling.</p>

authors

• Abdelmaksoud, Ahmed M
• Becker, Tracy
• Balomenos, Georgios

status

• published 

publication date

• 2019

published in

• IABSE Congress, New York, New York 2019: The Evolving Metropolis  Journal

presented at event

• IABSE Congress, New York, New York 2019: The Evolving Metropolis  Conference

keywords

• 33 Built Environment and Design
• 3302 Building
• 40 Engineering
• 4005 Civil Engineering

Digital Object Identifier (DOI)

• 10.2749/newyork.2019.0897

start page

• 897

end page

• 901

volume

• 115