Applications of optical fiber sensor in pavement Engineering: A review

Wang, Jiawei; Han, Yifeng; Cao, Zhenglong; Xu, Xiyong; Zhang, Jiake; Xiao, Feipeng

doi:10.1016/j.conbuildmat.2023.132713

Cited by 27 publications

(11 citation statements)

References 121 publications

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“…Table 4 shows results of the cost, error, and lifetime between different methods for axle load estimation [40]. The results show that the proposed method has advantages both in cost and lifetime.…”

Section: Comparison With the Different Axle Load Estimation Methodsmentioning

confidence: 99%

Temporal Convolutional Network-Based Axle Load Estimation from Pavement Vibration Data

Bian,

Zeng,

Zhao

et al. 2023

Applied Sciences

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Measuring the axle loads of vehicles with more accuracy is a crucial step in weight enforcement and pavement condition assessment. This paper proposed a vibration-based method, which has an extended sensing range, high temporal sampling rate, and dense spatial sampling rate, to estimate axle loads in concrete pavement using distributed optical vibration sensing (DOVS) technology. Temporal convolutional networks (TCN), which consist of non-causal convolutional layers and a concatenate layer, were proposed and trained by over 6000 samples of vibration data and ground truth of axle loads. Moreover, the TCN could learn the complex inverse mapping between pavement structure inputs and outputs. The performance of the proposed method was calibrated in two field tests with various conditions. The results demonstrate that the proposed method obtained estimated axle loads within 11.5% error, under diverse circumstances that consisted of different pavement types and loads moving at speeds ranging from 0~35 m/s. The proposed method demonstrates significant promise in the field of axle load reconstruction and estimation. Its error, closely approaching the 10% threshold specified by LTPP, underscores its efficacy. Additionally, the method aligns with the standards set by Cost-323, with an error level-up to category C. This indicates its capability to provide valuable support in the assessment and decision-making processes related to pavement structure conditions.

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Section: Comparison With the Different Axle Load Estimation Methodsmentioning

confidence: 99%

Temporal Convolutional Network-Based Axle Load Estimation from Pavement Vibration Data

Bian,

Zeng,

Zhao

et al. 2023

Applied Sciences

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“…Therefore, a fibreglass rod was instrumented with a series of FBG sensors and used as a support for the optic cable, and the set was then inserted in a groove cut in the pavement that was subsequently filled with an appropriate resin (QuiniResin Fix) [28] selected during the laboratory work. This approach for the post-installation of FBG sensors in road pavements, transversally to the traffic direction and embedded in a fibreglass rod (for protection), can be considered an innovative solution since no other similar application has been found in the literature, namely, in a recent review on this subject [29].…”

Section: Fibre Bragg Grating Coating and Protectionmentioning

confidence: 99%

Installation and Use of a Pavement Monitoring System Based on Fibre Bragg Grating Optical Sensors

Rebelo,

Oliveira,

Silva

et al. 2023

Infrastructures

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The evolution of technological tools, namely affordable sensors for data collection, and the growing concerns about maintaining roads in adequate conditions have promoted the development of continuous pavement monitoring systems. This paper presents the installation and use of an innovative pavement monitoring system, which was developed to measure the effects of vehicle loads and temperature on the performance of a pavement structure. The sensors used are based on fibre Bragg grating optical technology, collecting data about the strains imposed in the pavement and the temperature at which those measurements are made. The site selection for the system’s installation and the essential installation details to ensure successful data collection are addressed. A calibration procedure was implemented by performing falling weight deflectometer tests and passing preweighed heavy vehicles over the sensors. In addition to validating the system installation, the results obtained in the calibration confirmed the importance of adequately choosing the distance between sensors. Differences of 50 mm in the position of the load may cause differences of about 20% to 25% in the resulting strains. These results confirmed the importance of increasing the sensor concentration in wheel paths. Furthermore, for loads between 25 kN and 65 kN, raising the temperature by 8 °C caused an increase of about 20% in the horizontal tensile strains measured in the pavement. In summary, it was possible to conclude that this innovative system is capable of capturing the effects of temperature and vehicle speed on the response of the pavement, which may be considered an advantage of this type of monitoring system when compared to those that are only used to determine the loads applied to the pavement or to characterise the type of vehicle.

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“…Since the Strategic Highway Research Program (SHRP) in the United Table 1. Comparison of resistance sensor and FBG sensor in road structural health monitoring [26,28,29].…”

Section: Introductionmentioning

confidence: 99%

Sensor-Based Structural Health Monitoring of Asphalt Pavements with Semi-Rigid Bases Combining Accelerated Pavement Testing and a Falling Weight Deflectometer Test

Liu,

Cui,

Yang

et al. 2024

Sensors

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The Structural Health Monitoring (SHM) of pavement infrastructures holds paramount significance in the assessment and prognostication of the remaining service life of roadways. In response to this imperative, a methodology for surveilling the surface and internal mechanical responses of pavements was devised through the amalgamation of Accelerated Pavement Testing (APT) and Falling Weight Deflectometer (FWD) examinations. An experimental road segment, characterized by a conventional asphalt pavement structure with semi-rigid bases, was meticulously established in Jiangsu, China. Considering nine distinct influencing factors, including loading speed, loading weight, and temperature, innovative buried and layout configurations for Resistive Sensors and Fiber-optic Bragg Grating (FBG) sensors were devised. These configurations facilitated the comprehensive assessment of stress and strain within the road structure across diverse APT conditions. The methodology encompassed the formulation of response baselines, the conversion of electrical signals to stress and strain signals, and the proposition of a signal processing approach involving partial filtering and noise reduction. In experimental findings, the asphalt bottom layer was observed to undergo alternate tensile strains under dynamic loads (the peak strain was ten με). Simultaneously, the horizontal transverse sensor exhibited compressive strains peaking at 66.5 με. The horizontal longitudinal strain within the base and subbase ranged between 3 and 5 με, with the base registering a higher strain value than the subbase. When subjected to FWD, the sensor indicated a diminishing peak pulse signal, with the most pronounced peak response occurring when the load plate was situated atop the sensor. In summary, a comprehensive suite of monitoring schemes for road structures has been formulated, delineating guidelines for the deployment of road sensors and facilitating sustained performance observation over extended durations.

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Applications of optical fiber sensor in pavement Engineering: A review

Cited by 27 publications

References 121 publications

Temporal Convolutional Network-Based Axle Load Estimation from Pavement Vibration Data

Temporal Convolutional Network-Based Axle Load Estimation from Pavement Vibration Data

Installation and Use of a Pavement Monitoring System Based on Fibre Bragg Grating Optical Sensors

Sensor-Based Structural Health Monitoring of Asphalt Pavements with Semi-Rigid Bases Combining Accelerated Pavement Testing and a Falling Weight Deflectometer Test

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