Dynamic displacement monitoring of long-span bridges with a microwave radar interferometer

Zhang, Bochen; Ding, Xiaoli; Werner, Charles; Tan, Kai; Zhang, Bin; Jiang, Mi; Zhao, Junliang; Xu, You‐Lin

doi:10.1016/j.isprsjprs.2018.02.020

Cited by 51 publications

(29 citation statements)

References 40 publications

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“…Other vehicle classification methods such as laser Doppler vibrometers [148], vision-based methods [149,150], Microwave radar interferometer [151] are also used for SHM of bridge structure. Table 8 presented important studies conducted on vehicle-classification-based methods for SHM.…”

Section: Vehicle-classification-based Methodsmentioning

confidence: 99%

Vehicle-Assisted Techniques for Health Monitoring of Bridges

Shokravi

Bakhary

et al. 2020

Sensors

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Bridges are designed to withstand different types of loads, including dead, live, environmental, and occasional loads during their service period. Moving vehicles are the main source of the applied live load on bridges. The applied load to highway bridges depends on several traffic parameters such as weight of vehicles, axle load, configuration of axles, position of vehicles on the bridge, number of vehicles, direction, and vehicle’s speed. The estimation of traffic loadings on bridges are generally notional and, consequently, can be excessively conservative. Hence, accurate prediction of the in-service performance of a bridge structure is very desirable and great savings can be achieved through the accurate assessment of the applied traffic load in existing bridges. In this paper, a review is conducted on conventional vehicle-based health monitoring methods used for bridges. Vision-based, weigh in motion (WIM), bridge weigh in motion (BWIM), drive-by and vehicle bridge interaction (VBI)-based models are the methods that are generally used in the structural health monitoring (SHM) of bridges. The performance of vehicle-assisted methods is studied and suggestions for future work in this area are addressed, including alleviating the downsides of each approach to disentangle the complexities, and adopting intelligent and autonomous vehicle-assisted methods for health monitoring of bridges.

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Section: Vehicle-classification-based Methodsmentioning

confidence: 99%

Vehicle-Assisted Techniques for Health Monitoring of Bridges

Shokravi

Bakhary

et al. 2020

Sensors

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“…Zhang et al [12] focused on remote monitoring of vibration displacement responses of two long-span bridges using the Gamma portable radar interferometer, which is a developed multimode microwave interferometric radar system. Liu et al [13] monitored dynamic responses using ground-based microwave interferometry and then analyzed ancient bridge vibration using the extreme-point symmetric mode decomposition method.…”

Section: Introductionmentioning

confidence: 99%

A Plastic Optical Fiber Sensing System for Bridge Deflection Measurement

Yang

Wang

Ren

et al. 2020

Sensors

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Deflection is one of the key parameters that reflects the state of a bridge. However, deflection measurement is difficult for a bridge that is under operation. Most existing sensors and measuring techniques often do not meet the requirements for health monitoring for various types of bridges. Therefore, based on changes of optical fiber intensity, a novel sensing system using connected pipes to measure bridge deflection in different positions is proposed in this paper. As an absolute reference, the liquid level position along the structure is adopted for the deflection measurement, and an additional external reference to the ground is not needed in this system. The proposed system consists of three parts: connected pipes to connect the measurement points along the structure, liquid to fill in the connected pipes, and the sensing element to detect the change of level. A plastic optical fiber sensor based on the intensity change is used as the sensing element of the developed system. Then, a set of experimental tests are conducted for performance evaluation purposes. Results show that this system has an accurate linear response and high reliability under various environmental conditions. The deflection of the test beam measured by the sensor agrees with linear variable differential transformer (LVDT) within an error margin of 2.1%. The proposed system shows great potential applicability for future health monitoring of long-span bridges.

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“…Assessing the main natural frequencies and mode forms of the bridge is of particular importance [19]. They can also be monitored using GAMMA Portable Radar Interferometer (GPRI) [20]. The TTB model could also be used for testing rail bridge parameters, and shows that shorter wavelengths are important for safety analyses.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Dynamic Parameters of a Railway Bridge

et al. 2019

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This article analyses the dispersion of vibration accelerations of a railway bridge during the passage of a train, and presents an analysis of their parameters after the application of the theory of covariance functions. The measurements of vibration accelerations at the fixed points of the beams of the overlay of the bridge were recorded in the time scale as digital arrays (matrices). The values of inter-covariance functions of the arrays of data of measurements of digital vibration accelerations and the values of auto-covariance functions of the individual arrays, changing the quantization interval in the time scale, were calculated. The compiled software Matlab 7 in the operator package environment was used in calculations. This article aims at determining the interdependencies of results of vibrations of bridge points rather than at the impact which a train makes on a bridge without emphasizing the modal parameters of the bridge. The aforementioned interdependencies make it possible to predict the results of hard-to-reach points.

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Dynamic displacement monitoring of long-span bridges with a microwave radar interferometer

Cited by 51 publications

References 40 publications

Vehicle-Assisted Techniques for Health Monitoring of Bridges

Vehicle-Assisted Techniques for Health Monitoring of Bridges

A Plastic Optical Fiber Sensing System for Bridge Deflection Measurement

Analysis of Dynamic Parameters of a Railway Bridge

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