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Data Compression Approach for Long-Term Monitoring of Pavement Structures

Manosalvas-Paredes, Mario; Lajnef, Nizar; Chatti, Karim; Aono, Kenji; Blanc, Juliette; Thom, Nick; Airey, Gordon; Lo Presti, Davide

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Authors

Mario Manosalvas-Paredes

Nizar Lajnef

Karim Chatti

Kenji Aono

Juliette Blanc

NICK THOM NICHOLAS.THOM@NOTTINGHAM.AC.UK
Assistant Professor

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GORDON AIREY GORDON.AIREY@NOTTINGHAM.AC.UK
Professor of Pavement Engineering Materials

Davide Lo Presti



Abstract

Pavement structures are designed to withstand continuous damage during their design life. Damage starts as soon as the pavement is open to traffic and increases with time. If maintenance activities are not considered in the initial design or considered but not applied during the service life, damage will grow to a point where rehabilitation may be the only and most expensive option left. In order to monitor the evolution of damage and its severity in pavement structures, a novel data compression approach based on cumulative measurements from a piezoelectric sensor is presented in this paper. Specifically, the piezoelectric sensor uses a thin film of polyvinylidene fluoride to sense the energy produced by the micro deformation generated due to the application of traffic loads. Epoxy solution has been used to encapsulate the membrane providing hardness and flexibility to withstand the high-loads and the high-temperatures during construction of the asphalt layer. The piezoelectric sensors have been exposed to three months of loading (approximately 1.0 million loads of 65 kN) at the French Institute of Science and Technology for Transport, Development and Networks (IFSTTAR) fatigue carrousel. Notably, the sensors survived the construction and testing. Reference measurements were made with a commercial conventional strain gauge specifically designed for measurements in hot mix asphalt layers. Results from the carrousel successfully demonstrate that the novel approach can be considered as a good indicator of damage progression, thus alleviating the need to measure strains in pavement for the purpose of damage tracking.

Citation

Manosalvas-Paredes, M., Lajnef, N., Chatti, K., Aono, K., Blanc, J., Thom, N., …Lo Presti, D. (2019). Data Compression Approach for Long-Term Monitoring of Pavement Structures. Infrastructures, 5, Article 1. https://doi.org/10.3390/infrastructures5010001

Journal Article Type Article
Acceptance Date Dec 20, 2019
Online Publication Date Dec 22, 2019
Publication Date Dec 22, 2019
Deposit Date Jan 6, 2020
Publicly Available Date Jan 6, 2020
Journal Infrastructures
Print ISSN 2412-3811
Electronic ISSN 2412-3811
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 5
Article Number 1
DOI https://doi.org/10.3390/infrastructures5010001
Keywords Accelerated pavement testing (APT); Fatigue; Piezoelectric sensor; Pavement responses; Longitudinal strain
Public URL https://nottingham-repository.worktribe.com/output/3663698
Publisher URL https://www.mdpi.com/2412-3811/5/1/1

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