Analysis of data for 6,978 bridges to inform a data strategy for predictive maintenance

Stevens, Nicola-Ann; Lydon, Myra; Taylor, Su; Hamill, Gregory P.; Marshall, A.H.; Campbell, Kristopher; Neeson, Thomas; O’Connor, Alan

doi:10.1201/9780429279119-569

Cited by 1 publication

(1 citation statement)

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“…An exercise to calculate BCI values retrospectively based on the inspection data for inspections carried out between 1999 and 2017, allowed this historic data to be incorporated into a separate 'augmented' dataset. Details of this process are covered in work published by the authors [1]. This paper will use both the current bridge management data set and the augmented dataset at various points.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Arch Bridge Condition Data to Identify Network-Wide Controls and Trends

Campbell,

Lydon,

Stevens

et al. 2024

Infrastructures

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This paper outlines an initial analysis of 20 years of data held on an electronic bridge management database for approximately 3500 arch bridges across Northern Ireland (NI) by the Department for Infrastructure. Arch bridges represent the largest group of bridge types, making up nearly 56% of the total bridge stock in NI. This initial analysis aims to identify trends that might help inform maintenance decisions in the future. Consideration of the Bridge Condition Indicator (BCI) average value for the overall arch bridge stock indicates the potential for regional variations in the overall condition and the potential for human bias in inspections. The paper presents the most prevalent structural elements and associated defects recorded in the inspections of arch bridges. This indicated a link to scour and undermining for the worst-conditioned arch bridges. An Analysis of Variance (ANOVA) analysis identified function, number of spans, and deck width as significant factors during the various deterioration stages in a bridge’s lifecycle.

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Section: Introductionmentioning

confidence: 99%