Wireless monitoring of the longitudinal displacement of the Tamar Suspension Bridge deck under changing environmental conditions

Battista, Nicky de; Westgate, Robert; Koo, Ki-Young

doi:10.1117/12.879811

Cited by 9 publications

(8 citation statements)

References 8 publications

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“…Based on these measurements, a displacement model can be established and used to evaluate the state of the movable bearings. For instance, an abnormal change in the longitudinal displacements at a given pillar can indicate a problem with the corresponding movable bearing (de Battista et al, 2011;Wang et al, 2016;Webb et al, 2014;Yi et al, 2010). The main limitation of the latter method is that it can only monitor the displacements in correspondence of each pillar.…”

Section: Introductionmentioning

confidence: 99%

Displacement monitoring and modelling of a high-speed railway bridge using C-band Sentinel-1 data

Huang

Crosetto

Monserrat

et al. 2017

ISPRS Journal of Photogrammetry and Remote Sensing

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a b s t r a c tBridge displacement monitoring is one of the key components of bridge structural health monitoring. Traditional methods, usually based on limited sets of sensors mounted on a given bridge, collect pointlike deformation information and have the disadvantage of providing incomplete displacement information. In this paper, a Persistent Scatterer Interferometry (PSI) approach is used to monitor the displacements of the Nanjing Dashengguan Yangtze River high-speed railway bridge. Twenty-nine (29) European Space Agency Sentinel-1A images, acquired from April 25, 2015 to August 5, 2016, were used in the PSI analysis. A total of 1828 measurement points were selected on the bridge. The results show a maximum longitudinal displacement of about 150 mm on each side of the bridge. The measured displacements showed a strong correlation with the environmental temperature at the time the images used were acquired, indicating that they were due to thermal expansion of the bridge. At each pier, a regression model based on the PSI-measured displacements was compared with a model based on in-situ measurements. The good agreement of these models demonstrates the capability of the PSI technique to monitor long-span railway bridge displacements. By comparing the modelled displacements and dozens of PSI measurements, we show how the performance of movable bearings can be evaluated. The high density of the PSI measurement points is advantageous for the health monitoring of the entire bridge. Ó

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Section: Introductionmentioning

confidence: 99%

Displacement monitoring and modelling of a high-speed railway bridge using C-band Sentinel-1 data

Huang

Crosetto

Monserrat

et al. 2017

ISPRS Journal of Photogrammetry and Remote Sensing

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“…Other sensors that do not rely on line‐of‐sight capabilities are not without their own difficulties, and Battista et al. () commented on experiencing missing data due to cable infrastructure problems.…”

Section: Discussionmentioning

confidence: 99%

“…The image-processing algorithm used in this research is likely to be successful on this kind of similar images; this may be an area for future investigation. Other sensors that do not rely on line-of-sight capabilities are not without their own difficulties, and Battista et al (2011) commented on experiencing missing data due to cable infrastructure problems.…”

Section: Assessing the Accuracy Of The Systemmentioning

confidence: 99%

Monitoring 3D Vibrations in Structures using High‐resolution Blurred Imagery

McCarthy

Chandler

Palmeri

2016

The Photogrammetric Record

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Photogrammetry has been used in the past to monitor the laboratory testing of civil engineering structures using multiple image‐based sensors. This has been successful, but detecting vibrations during dynamic structural tests has proved more challenging because they usually depend on high‐speed cameras which often results in lower image resolutions and reduced accuracy. To overcome this limitation, a novel approach has been devised to take measurements from blurred images in long‐exposure photographs. The motion of the structure is captured in individual motion‐blurred images without dependence on imaging speed. A bespoke algorithm then determines each measurement point's motion. Using photogrammetric techniques, a model structure's motion with respect to different excitation frequencies is captured and its vibration envelope recreated in 3D. The approach is tested and used to identify changes in the model's vibration response.

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“…The major part of the cumulative sliding displacement is obtained from the vehicle‐induced dynamic displacement. In general, the displacement of bridge bearings is monitored by the displacement sensors with a frequency as small as 1 Hz or smaller . The low‐frequency displacement sensors cannot record the high‐frequency bearing displacement information.…”

Section: Introductionmentioning

confidence: 99%

“…In general, the displacement of bridge bearings is monitored by the displacement sensors with a frequency as small as 1 Hz or smaller. [16][17][18][19][20] The low-frequency displacement sensors cannot record the high-frequency bearing displacement information. Additionally, the main girder will vibrate with various modes, including relatively high-frequency modes, for practical bridges subject to vehicle/wind loads.…”

Section: Introductionmentioning

confidence: 99%

Sliding life prediction of sliding bearings using dynamic monitoring data of bridges

Yang

et al. 2020

Struct Control Health Monit

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Summary Sliding bearings of a bridge are important sliding elements that accommodate the bridge movement caused by temperature action and vehicle/wind load. The sliding life of sliding bearings is determined by the wear of the sliding materials in the bearing. However, the wear of sliding bearings primarily results from a large amount of cumulative sliding displacement experienced by the sliding bearing, even if the movement of the bridge under the vehicle/wind load is far less than the allowable design displacement of the sliding bearing. In general, bearing displacement is monitored using displacement gauges with a low sampling frequency, which cannot accurately capture the relatively high‐frequency displacement component caused by vehicle/wind loads. For predicting the sliding life of sliding bearings, this paper provides a mode rotation angle superposition approach to estimate cumulative sliding displacement. The estimation approach incorporates the combination of the rotation angles of bridge ends and the modal parameters of bridges. The feasibility and advantage of the estimation approach are illustrated by a numerical example; then, the influence factors of the error are analysed. Finally, sliding life prediction of sliding bearings is applied to an actual bridge using the estimation approach of cumulative sliding displacement.

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Wireless monitoring of the longitudinal displacement of the Tamar Suspension Bridge deck under changing environmental conditions

Cited by 9 publications

References 8 publications

Displacement monitoring and modelling of a high-speed railway bridge using C-band Sentinel-1 data

Displacement monitoring and modelling of a high-speed railway bridge using C-band Sentinel-1 data

Monitoring 3D Vibrations in Structures using High‐resolution Blurred Imagery

Sliding life prediction of sliding bearings using dynamic monitoring data of bridges

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