Structural Health Monitoring

Humar, J. L.; Amin, Mostafa S.

doi:10.1016/b978-008043948-8/50132-6

Cited by 6 publications

(7 citation statements)

References 2 publications

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“…The phenomenon of resistance varying with strain belongs to piezoresistive effect. Gauge factor (GF) is usually used to evaluate this property of materials, and it associates resistance change rate with external strain, as shown in equation (1). The slope of fitting line of the curve in Figure 3 equals the GF of the film.…”

Section: Electromechanical Properties Of the Rgo-cnf/wepmentioning

confidence: 99%

“…The service periods of concrete structures are usually several decades or even longer. In the long-term process, combined actions of multiple factors, such as load effect, environmental erosion, and material aging, will lead to damage accumulation and resistance attenuation of concrete structures [1,2]. If the crisis situation cannot be timely warned and repaired, it will easily lead to catastrophic accidents.…”

Section: Introductionmentioning

confidence: 99%

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A Three-Dimensional Strain Rosette Sensor Based on Graphene Composite with Piezoresistive Effect

Wei

Dong

et al. 2019

Journal of Sensors

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Obtaining the internal stress and strain state of concrete to evaluate the safety and reliability of structures is the important purpose of concrete structural health monitoring. In this paper, a three-dimensional (3D) strain rosette sensor was designed and fabricated using graphene-based piezoresistive composite to measure the strains in concrete structures. The piezoresistive composite was prepared using reduced graphene oxide (RGO) as conductive filler, cellulose nanofiber (CNF) as dispersant and structural skeleton, and waterborne epoxy (WEP) as polymer matrix. The mechanical, electrical, and electromechanical properties of RGO-CNF/WEP composite were tested. The results show that the tensile strength, elastic modulus, and conductivity of the composite are greatly improved by the addition of RGO and CNF. The relative resistance change of composite films demonstrates high sensitivity to mechanical strain with gauge factors of 16-52. Within 4% strain, the piezoresistive properties of composites are stable with good linearity and repeatability. The sensing performance of the 3D strain rosette was tested. The measured strains are close to the actual strains of measure point in concrete, and the error is small. The RGO-CNF/WEP composite has excellent mechanical and piezoresistive properties, which enable the 3D strain rosette to be used as embedded sensor to measure the internal strain of concrete structures accurately.

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Section: Electromechanical Properties Of the Rgo-cnf/wepmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Three-Dimensional Strain Rosette Sensor Based on Graphene Composite with Piezoresistive Effect

Wei

Dong

et al. 2019

Journal of Sensors

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“…The monitoring strategy is defined through a risk assessment survey that describes possible aging or failure causes and respective consequences [3]. Monitoring systems offer a wide range of technical options and associated costs: they may consist of, e.g., periodic human visual inspections, periodic or continuous measurement of a physical parameter with probes, and remote sensing surveys [4].…”

Section: Introductionmentioning

confidence: 99%

Toward Workable and Cost-Efficient Monitoring of Unstable Rock Compartments with Ambient Noise

Bottelin¹,

Baillet

Carrier³

et al. 2021

Geosciences

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Ambient Vibration-Based Structural Health Monitoring (AVB–SHM) studies on prone-to-fall rock compartments have recently succeeded in detecting both pre-failure damaging processes and reinforcement provided by bolting. The current AVB–SHM instrumentation layout is yet generally an overkill, creating cost and power issues and sometimes requiring advanced signal processing techniques. In this article, we paved the way toward an innovative edge-computing approach tested on ambient vibration records made during the bolting of a ~760 m3 limestone rock column (Vercors, France). First, we established some guidelines for prone-to-fall rock column AVB–SHM by comparing several basic, computing-efficient, seismic parameters (i.e., Fast Fourier Transform, Horizontal to Vertical and Horizontal to Horizontal Spectral Ratios). All three parameters performed well in revealing the unstable compartment’s fundamental resonance frequency. HHSR appeared as the most consistent spectral estimator, succeeding in revealing both the fundamental and higher modes. Only the fundamental mode should be trustfully monitored with HVSR since higher peaks may be artifacts. Then, the first application of a novelty detection algorithm on an unstable rock column AVB–SHM case study showed the following: the feasibility of automatic removing the adverse thermomechanical fluctuations in column’s dynamic parameters based on machine learning, as well as the systematic detection of clear, permanent change in column’s dynamic behavior after grout injection and hardening around the bolts (i1 and i2). This implementation represents a significant workload reduction, compared to physical-based algorithms or numerical twin modeling, and shows better robustness with regard to instrumentation gaps. We believe that edge-computing monitoring systems combining basic seismic signal processing techniques and automatic detection algorithms could help facilitate AVB–SHM of remote natural structures such as prone-to-fall rock compartments.

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“…The service life of a concrete structure lasts for several decades or even longer. In long-term processes, the combined actions of multiple factors, such as the load effect, environmental erosion, and material aging, will lead to damage accumulation and resistance attenuation [2,3,4]. Deformation and cracking are the most direct phenomena of structural damage [5,6].…”

Section: Introductionmentioning

confidence: 99%

Epoxy Composites with Reduced Graphene Oxide–Cellulose Nanofiber Hybrid Filler and Their Application in Concrete Strain and Crack Monitoring

Wei

Dong

et al. 2019

Sensors

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Advances in nanotechnology have provided approaches for the fabrication of new composite materials for sensing. Flexible sensors can make up for the shortcomings of traditional strain sensors in monitoring the surface strain and cracks of concrete structures. Using reduced graphene oxide (RGO) as a conductive filler, cellulose nanofiber (CNF) as a dispersant and structural skeleton, and waterborne epoxy (WEP) as a polymer matrix, a flexible composite material with piezoresistive effect was prepared by the solution blending and solvent evaporation method. The mechanical, electrical, and electromechanical properties of the composite were investigated. The results show that CNF can significantly improve the dispersion of RGO in the WEP matrix and help to form stable reinforcing and conductive networks, leading to great changes in the mechanical properties and resistivity of the composite. The composite film can withstand large deformations (>55% strain), and the resistance change rate demonstrates a high sensitivity to mechanical strain with a gauge factor of 34–71. Within a 4% strain range, the piezoresistive property of the composite is stable with good linearity and repeatability. The performance of the flexible film sensor made of the composite is tested and it can monitor the strain and crack of the concrete surface well.

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Structural Health Monitoring

Cited by 6 publications

References 2 publications

A Three-Dimensional Strain Rosette Sensor Based on Graphene Composite with Piezoresistive Effect

A Three-Dimensional Strain Rosette Sensor Based on Graphene Composite with Piezoresistive Effect

Toward Workable and Cost-Efficient Monitoring of Unstable Rock Compartments with Ambient Noise

Epoxy Composites with Reduced Graphene Oxide–Cellulose Nanofiber Hybrid Filler and Their Application in Concrete Strain and Crack Monitoring

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