Structural health monitoring system of the long-span bridges in Turkey

Baş, Selçuk; Apaydın, Nurdan Memişoğlu; İlki, Alper; Çatbaş, F. Necati

doi:10.1080/15732479.2017.1360365

Cited by 39 publications

(23 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results helped to verify the post-tensioning and the sound performance of the bridge during its first year of service life. Others monitored rotations on long-span cable supported and suspension bridge structures to better understand their long term performance [32][33][34][35]. In [36][37][38], researchers installed inclinometers at the supports of the test bridge to investigate the boundary conditions.…”

Section: Overview Of Bridge Damage Detection Methods Using Direct Rotmentioning

confidence: 99%

Bridge damage detection using rotation measurements – Experimental validation

Huseynov

Kim

O’Brien

et al. 2020

Mechanical Systems and Signal Processing

View full text Add to dashboard Cite

This paper presents a novel bridge condition assessment methodology using direct rotation measurements. Initially, numerical analyses are carried out to develop the theoretical basis of the proposed bridge damage detection methodology. As a result of this study the difference in rotation influence lines obtained for healthy and damaged bridge states is proposed as a damage indicator. The sensitivity of rotation to damage and the effect of sensor locations on sensor sensitivities are investigated. Subsequently, extensive laboratory experiments are conducted on a 5.4 m long simply supported bridge structure in an effort to validate the results from the numerical analyses. The test structure is instrumented with rotation sensors and axle detectors and loaded with a fouraxle moving vehicle. In this study, rotations are measured using high grade uniaxial accelerometers. The procedure of measuring rotations using accelerometers is explained within the scope of this study. To test the robustness of the proposed bridge condition assessment methodology, a wide range of single and multiple damage scenarios is investigated and the results from this study show that the proposed methodology can successfully identify damage on a bridge. For the model considered, damage as low as 7% change in stiffness over an extent of 2.5% bridge span is shown to be detectable.

show abstract

Section: Overview Of Bridge Damage Detection Methods Using Direct Rotmentioning

confidence: 99%

Bridge damage detection using rotation measurements – Experimental validation

Huseynov

Kim

O’Brien

et al. 2020

Mechanical Systems and Signal Processing

View full text Add to dashboard Cite

show abstract

“…where y t+T is the prediction value of period (t + T) and a t , b t , and c t are different model parameters: a t � 3s (1) t − 3s (2) t + s (3) t , c t � (a 2 /2(1 − a) 2 )(s (1) t − 2s (2) t + s (3) t ), and (1) t − 2(5 − 4a)s (2) t + (4 − 3a)s (3) t ], where s (1) t , s (2) t , and s (3) t are the first, second, and third smoothing exponents: s (1) t � a × y t + (1 − a)s (1) t−1 , s (2) t � a × s (1) t + (1 − a)s (2) t−1 , and s (3) t � a × s (2) t + (1 − a)s (3) t−1 . Additionally, the error analysis is usually used to measure the accuracy of time-series prediction using certain measures, such as the mean error (ME), the mean absolute error (MAE), and the root mean square error (RMSE).…”

Section: Time-series Analysismentioning

confidence: 99%

“…Contrary to the traditional structural appearance inspections and load tests, the predictive analytics of inservice bridge structural performance with SHM data mining can provide a perspective for online analysis and early warning. Actually, SHM has been widely used in largespan bridges and even some medium-span bridges, e.g., the Brooklyn Bridge in New York, the Sutong Bridge in China, and the first Bosphorus Bridge in Turkey [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Predictive Analytics of In‐Service Bridge Structural Performance from SHM Data Mining Perspective: A Case Study

Jin

Liu

Bin

et al. 2019

Shock and Vibration

View full text Add to dashboard Cite

In-service bridge structural performance analysis and prediction are usually complicated and challenging because of many unknown and uncertain factors. Contrary to the traditional structural appearance inspections and load tests, structural health monitoring (SHM) can provide a perspective for online analysis, prediction, and early warning. So far, SHM has been widely used in many bridge structures, and a lot of bridge SHM data have also been collected. However, the existing studies usually focus on some independent and unsystematic analysis methods, which are hard to use widely in engineering applications to reveal the overall structural performance. This study focuses on the structural performance analysis and prediction of the highway in-service bridge. The dynamic problems in bridge SHM are pointed out firstly, followed by a detailed analysis about the characteristics of bridge SHM data. With the consideration of different characteristics, three targeted analysis methods are proposed. An urban concrete-filled steel tube (CFST) truss girder bridge (opened to traffic in 1995) is also presented, which once experienced some prominent vibration problems. The bridge SHM system is designed and stalled after several appearance inspections, load tests, and some reinforcement measures. The data mining methods proposed (distribution function, association analysis, and time-series analysis) are employed for the analysis and prediction of structural response and deterioration extent. This study can provide some references for maintenance and management and can also build a foundation for further online analysis and early warning.

show abstract

“…Moreover, experiences in the lab with microelectromechanical systems (MEMS) inclinometers for inter-story drift assessment [ 27 ], numerical analyses of beam-like bridge loaded with moving point load [ 28 ] or on-site analysis of progressive damage bridge case studies with different rotation measurements confirmed the sensitivity of rotation as a parameter for damage identification (e.g., among others [ 29 , 30 , 31 ]) that open new perspectives for seismic structural health monitoring of civil engineering buildings.…”

Section: Introductionmentioning

confidence: 97%

Comparing Direct Observation of Torsion with Array-Derived Rotation in Civil Engineering Structures

Guéguen

Guattari

Aubert

et al. 2020

Sensors

View full text Add to dashboard Cite

In this article, we analyze the rotation rates in a building derived from a network of translation sensors and recorded by a rotation sensor. The building is Grenoble city hall, a reinforced concrete structure with permanent accelerometric translation sensors at the top and bottom of the building. A temporary experiment was conducted, consisting in installing a BlueSeis-3A rotation sensor for more than 24 h at the top of the structure. The ambient vibrations were analyzed. The amplitudes of translation accelerations and rotation rates at the top and bottom of the building, along with their variations over time, were analyzed. The acceleration/rotation ratios were then compared with the impulse wave velocities derived from seismic interferometry by deconvolution between the top and bottom. Perspectives with regard to building imaging, time monitoring of structural integrity and understanding the contribution of rotations to the structure’s response are discussed, offering new suggestions for research projects.

show abstract

Structural health monitoring system of the long-span bridges in Turkey

Cited by 39 publications

References 27 publications

Bridge damage detection using rotation measurements – Experimental validation

Bridge damage detection using rotation measurements – Experimental validation

Predictive Analytics of In‐Service Bridge Structural Performance from SHM Data Mining Perspective: A Case Study

Comparing Direct Observation of Torsion with Array-Derived Rotation in Civil Engineering Structures

Contact Info

Product

Resources

About