Smart reinforcement steel bars with low-cost MEMS sensors for the structural health monitoring of RC structures

Tondolo, Francesco; Cesetti, Alessandro; Matta, Emiliano; Quattrone, Antonino; Sabia, Donato

doi:10.1016/j.conbuildmat.2018.04.045

Cited by 15 publications

(20 citation statements)

References 9 publications

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“…Conventional strain gauges and FOS can be damaged in service due to the formation of cracks in reinforced concrete or slip between steel and concrete. Tondolo et al [92] proposed a new scheme to monitor axial strain by combining embedded MEMS sensors to measure pressure and temperature changes. Moreover, MEMS embedded in concrete can help engineers monitor the solidification of concrete more effectively.…”

Section: Applicationsmentioning

confidence: 99%

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The Application of Advanced Information Technologies in Civil Infrastructure Construction and Maintenance

Guo

et al. 2022

Sustainability

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Information technologies have widely been used in the construction and maintenance of civil infrastructure. The advantages of information technologies provided a broader range of methods for infrastructure and enhanced its level of maintenance. However, a systematic summary of the research development of information technologies used in civil infrastructure is limited. This study aims to supplement this field by providing an objective, systematic summary of relevant literature in mainstream journals employing bibliometric retrieval and quantitative analysis from 2010 to 2020. The following results are obtained: (1) This study discusses the application of advanced information technologies in different phases and provides a critical analysis of the application of these existing information technologies, which includes wireless sensor networks (WSN), fiber optic sensing (FOS), building information modelling (BIM), radio frequency identification (RFID) and other advanced information technologies. (2) The digital twins can be used as tools for the planning and management of next-generation smart infrastructure, making the future of civil infrastructure smarter and more sustainable.

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Section: Applicationsmentioning

confidence: 99%

“…FOS 6. MEMS (Strain monitoring [58]) (Assessment performance and condition [130], SHM [91,92,131]) 7. ICT, AI 7.…”

Section: Application Of Information Technologies In Different Phasesmentioning

confidence: 99%

The Application of Advanced Information Technologies in Civil Infrastructure Construction and Maintenance

Guo

et al. 2022

Sustainability

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“…MEMS are used to measure the magnitude of diverse variables, such as acceleration [127,132], angular velocity (gyroscopes) [133], displacement [134], and deformation [135]. This type of sensor offers high sensitivity [127], responses at low frequencies [136], the measurement of multiple variables, and the integration of communication systems [137].…”

Section: Microelectromechanical Systems (Mems)mentioning

confidence: 99%

Damage Identification in Structural Health Monitoring: A Brief Review from its Implementation to the Use of Data-Driven Applications

Burgos

Vargas

Pedraza

et al. 2020

Sensors

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The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.

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“…The knowledge of the full-field displacements implies that further structural response, such as the stress field, can be reconstructed, thus enabling real-time damage prediction by means of proper failure criteria. Furthermore, the advances in the microelectromechanical system (MEMS) field have made this possible with low-cost devices [ 2 , 3 ]. Embedded systems are also welcome because they can be protected into the structure against the aggressive external environment that causes failures in traditional external systems.…”

Section: Introductionmentioning

confidence: 99%

Shape-Sensing of Beam Elements Undergoing Material Nonlinearities

Savino

Gherlone

Tondolo

et al. 2021

Sensors

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The use of in situ strain measurements to reconstruct the deformed shape of structures is a key technology for real-time monitoring. A particularly promising, versatile and computationally efficient method is the inverse finite element method (iFEM), which can be used to reconstruct the displacement field of beam elements, plate and shell structures from some discrete strain measurements. The iFEM does not require the knowledge of the material properties. Nevertheless, it has always been applied to structures with linear material constitutive behavior. In the present work, advances are proposed to use the method also for concrete structures in civil engineering field such as bridges normally characterized by material nonlinearities due to the behavior of both steel and concrete. The effectiveness of iFEM, for simply supported reinforced concrete beam and continuous beams with load conditions that determine the yielding of reinforcing steel, is studied. In order to assess the influence on displacements and strains reconstructions, different measurement stations and mesh configurations are considered. Hybrid procedures employing iFEM analysis supported by bending moment-curvature relationship are proposed in case of lack of input data in plastic zones. The reliability of the results obtained is tested and commented on to highlight the effectiveness of the approach.

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Smart reinforcement steel bars with low-cost MEMS sensors for the structural health monitoring of RC structures

Cited by 15 publications

References 9 publications

The Application of Advanced Information Technologies in Civil Infrastructure Construction and Maintenance

The Application of Advanced Information Technologies in Civil Infrastructure Construction and Maintenance

Damage Identification in Structural Health Monitoring: A Brief Review from its Implementation to the Use of Data-Driven Applications

Shape-Sensing of Beam Elements Undergoing Material Nonlinearities

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