An RFID-Enabled Wireless Strain Gauge Sensor for Static and Dynamic Structural Monitoring

Giampaolo, E. Di; Carlofelice, Alessandro Di; Gregori, Amedeo

doi:10.1109/jsen.2016.2631259

Cited by 40 publications

(33 citation statements)

References 21 publications

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“…By simply conglomerating several 2D images of a site, an intuitive and efficient method for understanding problems on a structure or existing sensor networks is not guaranteed. Additionally, as more advanced sensor networks are developed such as sensing sheets, skins, and other methods (Sabra et al, 2008;Loh et al, 2009;Zonta et al, 2009;Yao and Glisic, 2015;DiGiampaolo et al, 2017) it will become increasingly harder to clearly convey the space using 2D methods (Carno, 2017). This is not an issue for only visualizing SHM networks.…”

Section: Review Of Current Methodologies and Existing Gapsmentioning

confidence: 99%

Combination of Image-Based Documentation and Augmented Reality for Structural Health Monitoring and Building Pathology

Napolitano

Liu

Sun

et al. 2019

Front. Built Environ.

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With the current deterioration rate of existing infrastructure, the importance of intervention and preservation efforts such as on-site visual inspections, non-destructive evaluation, structural health monitoring (SHM), and building pathology are on the rise. A critical aspect of these intervention and preservation methods is the visualization and accessibility of large, heterogeneous data sets. To enable diverse stakeholders to make informed choices, data and metadata for the built environment needs to be directly integrated into a user's viewing environment. To address this challenge, a human-machine interface which organizes these types of data and provides actionable information is necessary. The main aim of this work is to develop a preliminary framework for documenting and visualizing data about the built environment both on and off site using a combination of image-based documentation and augmented reality (AR). While this work illustrates preliminary annotation mechanisms such as drawing, the concept of projecting data between the image-based environment and the AR environment is the main contribution of this work. This method was applied to test objects as well as case studies in SHM and building pathology.

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Section: Review Of Current Methodologies and Existing Gapsmentioning

confidence: 99%

Combination of Image-Based Documentation and Augmented Reality for Structural Health Monitoring and Building Pathology

Napolitano

Liu

Sun

et al. 2019

Front. Built Environ.

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“…In the proposed wireless system, instead, the resistance-to-frequency technique is used in order to codify the strain measurement into a modulation frequency while preserving the high sensitivity of the Wheatstone bridge. A deeper description of the resistanceto-frequency converter is provided in [30].…”

Section: Methodsmentioning

confidence: 99%

“…This was confirmed also for different materials. About the weak nonlinearity of the experimental curve, it is worth to note that it mainly depends on the actual value of the hardware parameters, i.e., the tolerances of the electronic components (in particular, resistances and capacitances) that make the response of the sensor tag not perfectly linear as explained in [30]. Fortunately, the level of nonlinearity can be made small by means of an accurate choice of the electronic components so that the resulting nonlinearity can be ignored as shown by the R 2 value calculated for the linear regression plotted in Figure 7, approaching unit.…”

Section: Experimental Data From the Wireless Method: Staticmentioning

confidence: 99%

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Presenting a New Wireless Strain Method for Structural Monitoring: Experimental Validation

et al. 2019

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The structural health monitoring (SHM) of large and complex infrastructures as well as laboratory tests of new structures and materials resorts to strain gauge measurements to check mechanical stress. A wireless measurement of the strain gauge response is desirable in many practical applications to avoid the cost and the difficulty of wiring, particularly in large structures requiring several sensors and in complex objects where the measurement points are difficult to access. In this paper, a wireless strain gauge which is a hybrid between an RFID tag and a usual thin-film resistive strain gauge is experimented. Installation and maintenance problems of the wireless sensor networks are overcome allowing a high level of measurement accuracy, comparable to that of wired strain sensors, together with a long measurement distance. A large set of measurements has been performed using reference specimens and readings in order to validate the sensor and to develop a calibration procedure that makes the sensor suitable for a large number of different applications in civil engineering.

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“…In recent years, researchers show an increasing interest in wireless passive sensor technology [4][5][6][7][8][9][10][11], since it does not need battery supply and is maintenance free. Compared with the traditional wireless sensing technologies [12][13][14], wireless passive sensors could have a long operational life cycle, which is feasible for harsh environment applications.…”

Section: Introductionmentioning

confidence: 99%

An Impedance-Loaded Orthogonal Frequency-Coded SAW Sensor for Passive Wireless Sensor Networks

Dai

Fang

Zhang

et al. 2020

Sensors

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A passive wireless impedance-loaded orthogonal frequency-coded (OFC) surface acoustic wave (SAW) sensor for wireless sensor networks was proposed in this paper. One of the chips on OFC SAW tag is connected to an external sensor, which could cause a phase shift in the time response of the corresponding part on the SAW device. The phase shift corresponds to the sensed quantity, which could be temperature, strain, vibration, pressure, etc. The OFC SAW tag is isolated by a proper package from the direct effect of the measurand on the device’s response which could avoid the multiple measurands coupling. The simultaneous work of multiple sensors is guaranteed by orthogonal frequency coding. By processing the response based on an extended matched filter algorithm, sensing information of the specific coded OFC device can be extracted from the superimposed response of multiple independent encoded sensors. Compared to previous methods, the proposed method can produce a more flexible passive (battery-free) wireless sensor suitable for large-scale wireless sensor networks. Simulation and experimental results demonstrate the effectiveness of the sensor.

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An RFID-Enabled Wireless Strain Gauge Sensor for Static and Dynamic Structural Monitoring

Cited by 40 publications

References 21 publications

Combination of Image-Based Documentation and Augmented Reality for Structural Health Monitoring and Building Pathology

Combination of Image-Based Documentation and Augmented Reality for Structural Health Monitoring and Building Pathology

Presenting a New Wireless Strain Method for Structural Monitoring: Experimental Validation

An Impedance-Loaded Orthogonal Frequency-Coded SAW Sensor for Passive Wireless Sensor Networks

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