Maintenance strategies based on structural health monitoring can provide effective support in the optimization of scheduled repair of existing structures, thus enabling their lifetime to be extended. With specific regard to reinforced concrete (RC) structures, the state of the art seems to still be lacking an efficient and cost-effective technique capable of monitoring material properties continuously over the lifetime of a structure. Current solutions can typically only measure the required mechanical variables in an indirect, but economic, manner, or directly, but expensively. Moreover, most of the proposed solutions can only be implemented by means of manual activation, making the monitoring very inefficient and then poorly supported. This paper proposes a structural health monitoring system based on a wireless sensor network (WSN) that enables the automatic monitoring of a complete structure. The network includes wireless distributed sensors embedded in the structure itself, and follows the monitoring-based maintenance (MBM) approach, with its ABCDE paradigm, namely: accuracy, benefit, compactness, durability, and easiness of operations. The system is structured in a node level and has a network architecture that enables all the node data to converge in a central unit. Human control is completely unnecessary until the periodic evaluation of the collected data. Several tests are conducted in order to characterize the system from a metrological point of view and assess its performance and effectiveness in real RC conditions.

An embedded wireless sensor network with wireless power transmission capability for the structural health monitoring of reinforced concrete structures / Gallucci, Luca; Menna, Costantino; Angrisani, Leopoldo; Asprone, Domenico; Lo Moriello, Rosario Schiano; Bonavolontá, Francesco; Fabbrocino, Francesco. - In: SENSORS. - ISSN 1424-8220. - 17:11(2017), p. 2566. [10.3390/s17112566]

An embedded wireless sensor network with wireless power transmission capability for the structural health monitoring of reinforced concrete structures

GALLUCCI, LUCA;Menna, Costantino;Angrisani, Leopoldo;Asprone, Domenico;Lo Moriello, Rosario Schiano;Bonavolontá, Francesco;Fabbrocino, Francesco
2017

Abstract

Maintenance strategies based on structural health monitoring can provide effective support in the optimization of scheduled repair of existing structures, thus enabling their lifetime to be extended. With specific regard to reinforced concrete (RC) structures, the state of the art seems to still be lacking an efficient and cost-effective technique capable of monitoring material properties continuously over the lifetime of a structure. Current solutions can typically only measure the required mechanical variables in an indirect, but economic, manner, or directly, but expensively. Moreover, most of the proposed solutions can only be implemented by means of manual activation, making the monitoring very inefficient and then poorly supported. This paper proposes a structural health monitoring system based on a wireless sensor network (WSN) that enables the automatic monitoring of a complete structure. The network includes wireless distributed sensors embedded in the structure itself, and follows the monitoring-based maintenance (MBM) approach, with its ABCDE paradigm, namely: accuracy, benefit, compactness, durability, and easiness of operations. The system is structured in a node level and has a network architecture that enables all the node data to converge in a central unit. Human control is completely unnecessary until the periodic evaluation of the collected data. Several tests are conducted in order to characterize the system from a metrological point of view and assess its performance and effectiveness in real RC conditions.
2017
An embedded wireless sensor network with wireless power transmission capability for the structural health monitoring of reinforced concrete structures / Gallucci, Luca; Menna, Costantino; Angrisani, Leopoldo; Asprone, Domenico; Lo Moriello, Rosario Schiano; Bonavolontá, Francesco; Fabbrocino, Francesco. - In: SENSORS. - ISSN 1424-8220. - 17:11(2017), p. 2566. [10.3390/s17112566]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/705088
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