Browsing by Keyword "info:eu-repo/grantAgreement/EC/H2020/690660/EU/Risk based approaches for Asset inteGrity multimodal Transport Infrastructure ManagEment/RAGTIME"
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Item Bearing assessment tool for longitudinal bridge performance(2020-11-01) Garcia-Sanchez, David; Fernandez-Navamuel, Ana; Sánchez, Diego Zamora; Alvear, Daniel; Pardo, David; Tecnalia Research & Innovation; E&I SEGURAS Y RESILIENTESThis 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.Item Gradient-Boosting Applied for Proactive Maintenance System in a Railway Bridge(Springer, Cham, 2021) García-Sánchez, David; Iglesias, Francisco; Diez, Jesus; Piñero, Iñaki; Fernández-Navamuel, Ana; Sánchez, Diego Zamora; Jiménez-Fernandez, José Carlos; Rizzo, Piervincenzo; Milazzo, Alberto; Tecnalia Research & Innovation; E&I SEGURAS Y RESILIENTESThis article contributes in the research direction of the application of Machine Learning techniques in bridge safety assessment and it lays basis to further improve the accuracy of safety assessment including analysis of real data. The communication puts forward the process and model of scale measured points correlation of bridge monitoring system on the frequency domain as a tactic to control the influence of a railway device (crossing) located on the top deck of a railway bridge. The process and model are put forward mainly for the characteristics of the damage detection for long-term assessment, going from an intensive multi-sensor monitoring system to a softer one. Finally, a Gradient-Boosting multi-regressor method has been developed to be easily implemented in a warning system that provides predictive skills to the current preventive maintenance strategy. The method is validated by simulating the undamaged and abnormal scenarios with Monte Carlo method.