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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


Mario Manosalvas-Paredes

Nizar Lajnef

Karim Chatti

Kenji Aono

Juliette Blanc

Assistant Professor

Professor of Pavement Engineering Materials

Davide Lo Presti


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.

Journal Article Type Article
Publication Date Dec 22, 2019
Journal Infrastructures
Print ISSN 2412-3811
Electronic ISSN 2412-3811
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 5
Article Number 1
APA6 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,
Keywords Accelerated pavement testing (APT); Fatigue; Piezoelectric sensor; Pavement responses; Longitudinal strain
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