6533b7d9fe1ef96bd126d55a

RESEARCH PRODUCT

Condition Assessment of Norwegian Bridge Elements Using Existing Damage Records

Ephrem TaddesseAndreu Regué Barrufet

subject

Set (abstract data type)Artificial neural networkComputer sciencelanguageNorwegianData miningcomputer.software_genreCondition assessmentBridge (interpersonal)computerlanguage.human_languageArtificial neural network classifier

description

The Norwegian Public Roads Administration (NPRA) has recorded bridge element damages in a database for all the bridges it manages since the 1990s. This paper presents a comparison of three methods to establish element condition based on damage records. The methods consist in a non-parametric procedure based on the worst damage registered in the element, linear regression considering also bridge and road characteristics data and classification through an artificial neural network. The methods are assessed using a set of 159 bridges inspected in 2016. The results show that diagnostics of bridge element condition can reach high accuracy by using an artificial neural network classifier and taking into account existing damage records and bridge data.

yearjournalcountryeditionlanguage
2020-01-01
https://doi.org/10.1007/978-3-030-48021-9_79