Bearing assessment tool for longitudinal bridge performance
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ORIGINAL PAPER
Bearing assessment tool for longitudinal bridge performance David Garcia‑Sanchez1,3 · Ana Fernandez‑Navamuel1,2,4 · Diego Zamora Sánchez1 · Daniel Alvear3 · David Pardo4,2,5 Received: 26 February 2020 / Revised: 24 July 2020 / Accepted: 18 August 2020 © The Author(s) 2020
Abstract This work provides an unsupervised learning approach based on a single-valued performance indicator to monitor the global behavior of critical components in a viaduct, such as bearings. We propose an outlier detection method for longitudinal displacements to assess the behavior of a singular asymmetric prestressed concrete structure with a 120 m high central pier acting as a fixed point. We first show that the available long-term horizontal displacement measurements recorded during the undamaged state exhibit strong correlations at the different locations of the bearings. Thus, we combine measurements from four sensors to design a robust performance indicator that is only weakly affected by temperature variations after the application of principal component analysis. We validate the method and show its efficiency against false positives and negatives using several metrics: accuracy, precision, recall, and F1 score. Due to its unsupervised learning scope, the proposed technique is intended to serve as a real-time supervision tool that complements maintenance inspections. It aims to provide support for the prioritization and postponement of maintenance actions in bridge management. Keywords Structural health monitoring (SHM) · Principal component analysis · Damage detection
1 Introduction Electronic supplementary material The online version of this article (https://doi.org/10.1007/s13349-020-00432-1) contains supplementary material, which is available to authorized users. * David Garcia‑Sanchez [email protected] Ana Fernandez‑Navamuel ana.fernandez‑[email protected] Diego Zamora Sánchez [email protected] Daniel Alvear [email protected] David Pardo [email protected] 1
TECNALIA, Basque Research and Technology Alliance (BRTA), Parque Científico y Tecnológico de Bizkaia Astondo Bidea Edificio 700, 48160 Derio, Spain
2
Basque Center for Applied Mathematics (BCAM), Bilbao, Spain
3
University of Cantabria (UC), Santander, Spain
4
University of the Basque Country (UPV/EHU), Leioa, Spain
5
Ikerbasque (Basque Foundation for Sciences), Bilbao, Spain
Over the last decades, monitoring systems have gained importance in our society [1, 2]. Their main objective is to provide quantitative information on the performance of structures under service conditions to optimize the maintenance programs and avoid severe failures [3]. In the management of civil engineering structures, there are some elements whose correct behavior is critical in the planning of repair and substitution actions due to the high technical and economic costs. Some of these crucial components are bearings, particularly when they employ newly developed technologies or are installed in bridges with unconventional de
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