• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.2
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• pp.170-178
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• 2011

In this paper, a research was performed to develop a wireless measurement system for bridge monitoring using MEMS sensor and bluetooth wireless communication module. First, in order to prove the suitability of MEMS sensor for the bridge measurement, its ranges of measuring acceleration and of frequency response were experimented. Also, the quality of wireless communication was tested by an experiment on long-distance communication for the knowledge of maximum communication distance, and also by an experiment on the data transmit-receive capability both inside and outside of a steel box bridge. Later, placing the wireless acceleration sensor system that had been developed in our lab on a bridge in public service, we acquired vibration data from the bridge under traffic load and analyzed its dynamic characteristics in realtime. For the analysis of the data, NExT & ERA algorithm were employed. The result of analysis was compared to the FE analysis of the same bridge, and the comparison made it possible to evaluate the performance of wireless acceleration sensor system. As a result, it was proven that the wireless acceleration sensor system developed with the use of MEMS sensor and bluetooth wireless communication module could be effectively applied to the measurement of structure whose vibration feature was low frequency like a bridge.

• Smart Structures and Systems
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• v.15 no.3
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• pp.665-682
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• 2015

Structural identification or St-Id is 'the parametric correlation of structural response characteristics predicted by a mathematical model with analogous characteristics derived from experimental measurements'. This paper describes a St-Id exercise on Humber Bridge that adopted a novel two-stage approach to first calibrate and then validate a mathematical model. This model was then used to predict effects of wind and temperature loads on global static deformation that would be practically impossible to observe. The first stage of the process was an ambient vibration survey in 2008 that used operational modal analysis to estimate a set of modes classified as vertical, torsional or lateral. In the more recent second stage a finite element model (FEM) was developed with an appropriate level of refinement to provide a corresponding set of modal properties. A series of manual adjustments to modal parameters such as cable tension and bearing stiffness resulted in a FEM that produced excellent correspondence for vertical and torsional modes, along with correspondence for the lower frequency lateral modes. In the third stage traffic, wind and temperature data along with deformation measurements from a sparse structural health monitoring system installed in 2011 were compared with equivalent predictions from the partially validated FEM. The match of static response between FEM and SHM data proved good enough for the FEM to be used to predict the un-measurable global deformed shape of the bridge due to vehicle and temperature effects but the FEM had limited capability to reproduce static effects of wind. In addition the FEM was used to show internal forces due to a heavy vehicle to to estimate the worst-case bearing movements under extreme combinations of wind, traffic and temperature loads. The paper shows that in this case, but with limitations, such a two-stage FEM calibration/validation process can be an effective tool for performance prognosis.

• Smart Structures and Systems
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• v.17 no.3
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• pp.363-389
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• 2016

Deficient modes that cannot be always identified from different sets of measurement data may exist in the application of operational modal analysis such as the stochastic subspace identification techniques in large-scale civil structures. Based on a recent work using the long-term ambient vibration measurements from an instrumented cable-stayed bridge under different wind excitation conditions, a benchmark problem is launched by taking the same bridge as a test bed to further intensify the exploration of mode identifiability. For systematically assessing this benchmark problem, a recently developed SSI algorithm based on an alternative stabilization diagram and a hierarchical sifting process is extended and applied in this research to investigate several sets of known and blind monitoring data. The evaluation of delicately selected cases clearly distinguishes the effect of traffic excitation on the identifiability of the targeted deficient mode from the effect of wind excitation. An additional upper limit for the vertical acceleration amplitude at deck, mainly induced by the passing traffic, is subsequently suggested to supplement the previously determined lower limit for the wind speed. Careful inspection on the shape vector of the deficient mode under different excitation conditions leads to the postulation that this mode is actually induced by the motion of the central tower. The analysis incorporating the tower measurements solidly verifies this postulation by yielding the prevailing components at the tower locations in the extended mode shape vector. Moreover, it is also confirmed that this mode can be stably identified under all the circumstances with the addition of tower measurements. An important lesson learned from this discovery is that the problem of mode identifiability usually comes from the lack of proper measurements at the right locations.

• Smart Structures and Systems
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• v.19 no.6
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• pp.653-663
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• 2017

The modal parameters of the deck of Runyang Suspension Bridge (RSB) as well as their relationships with wind and temperature are studied based on the data recorded by its Structural Health Monitoring System (SHMS). Firstly, frequency analysis on the vertical responses at the two sides of the deck is carried out to distinguish the vertical and torsional vibration modes. Then, the vertical, torsional and lateral modal parameters of the deck of RSB are identified using Hilbert-Huang Transform (HHT) and validated by the identified results before RSB was opened to traffic. On the basis of this, the modal frequencies and damping ratios of RSB during the whole process of Typhoon Masta are obtained. And the correlation analysis on the modal parameters and wind environmental factors is then conducted. Results show that the HHT can achieve an accurate modal identification of RSB and the damping ratios show an obvious decay trend as the frequencies increase. Besides, compared to frequencies, the damping ratios are more sensitive to the environmental factors, in particular, the wind speed. Further study on configuring the variation law of modal parameters related with environmental factors should be continued.

• Structural Monitoring and Maintenance
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• v.4 no.4
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• pp.331-350
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• 2017

Based on the alternative stabilization diagram by varying the time lag parameter in the stochastic subspace identification analysis, this study aims to investigate the measurements from several cases of civil structures for extending the applicability of a recently noticed criterion to ensure stable identification results. Such a criterion demands the time lag parameter to be no less than a critical threshold determined by the ratio of the sampling rate to the fundamental system frequency and is firstly validated for its applications with single measurements from stay cables, bridge decks, and buildings. As for multiple measurements, it is found that the predicted threshold works well for the cases of stay cables and buildings, but makes an evident overestimation for the case of bridge decks. This discrepancy is further explained by the fact that the deck vibrations are induced by multiple excitations independently coming from the passing traffic. The cable vibration signals covering the sensor locations close to both the deck and pylon ends of a cable-stayed bridge provide convincing evidences to testify this important discovery.

• Smart Structures and Systems
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• v.15 no.3
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• pp.683-698
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• 2015

Railroad bridges form an integral part of railway infrastructure throughout the world. To accommodate increased axel loads, train speeds, and greater volumes of freight traffic, in the presence of changing structural conditions, the load carrying capacity and serviceability of existing bridges must be assessed. One way is through system identification of in-service railroad bridges. To dates, numerous researchers have reported system identification studies with a large portion of their applications being highway bridges. Moreover, most of those models are calibrated at global level, while only a few studies applications have used globally and locally calibrated model. To reach the global and local calibration, both ambient vibration tests and controlled tests need to be performed. Thus, an approach for system identification of a railroad bridge that can be used to assess the bridge in global and local sense is needed. This study presents system identification of a railroad bridge using free vibration data. Wireless smart sensors are employed and provided a portable way to collect data that is then used to determine bridge frequencies and mode shapes. Subsequently, a calibrated finite element model of the bridge provides global and local information of the bridge. The ability of the model to simulate local responses is validated by comparing predicted and measured strain in one of the diagonal members of the truss. This research demonstrates the potential of using measured field data to perform model calibration in a simple and practical manner that will lead to better understanding the state of railroad bridges.

• Structural Engineering and Mechanics
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• v.40 no.4
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• pp.471-488
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• 2011

The Ting Kau Bridge in Hong Kong is a cable-stayed bridge comprising two main spans and two side spans. The bridge deck is supported by three towers, an end pier and an abutment. Each of the three towers consists of a single reinforced concrete mast strengthened by transverse cables and struts. The bridge deck is supported by four inclined planes of cables emanating from anchorages at the tower tops. In view of the heavy traffic on the bridge, and threats from typhoons and earthquakes originated in areas nearby, the dynamic behaviour of long-span cable-supported bridges in the region is always an important consideration in their design. Baseline finite element models of various levels of sophistication have been built not only to match the bridge geometry and cable forces specified on the as-constructed drawings but also to be calibrated using the vibration measurement data captured by the Wind and Structural Health Monitoring System. This paper further describes the analysis of axle loading data, as well as the generation of random axle loads and simulation of vibrations of the bridge using the finite element models. Various factors affecting the vehicular loading on the bridge will also be examined.

• Smart Structures and Systems
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• v.10 no.2
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• pp.131-154
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• 2012

In this paper, it is aimed to determine the seismic behaviour of highway bridges by nondestructive testing using ambient vibration measurements. Eynel Highway Bridge which has arch type structural system with a total length of 216 m and located in the Ayvaclk county of Samsun, Turkey is selected as an application. The bridge connects the villages which are separated with Suat U$\breve{g}$urlu Dam Lake. A three dimensional finite element model is first established for a highway bridge using project drawings and an analytical modal analysis is then performed to generate natural frequencies and mode shapes in the three orthogonal directions. The ambient vibration measurements are carried out on the bridge deck under natural excitation such as traffic, human walking and wind loads using Operational Modal Analysis. Sensitive seismic accelerometers are used to collect signals obtained from the experimental tests. To obtain experimental dynamic characteristics, two output-only system identification techniques are employed namely, Enhanced Frequency Domain Decomposition technique in the frequency domain and Stochastic Subspace Identification technique in time domain. Analytical and experimental dynamic characteristic are compared with each other and finite element model of the bridge is updated by changing of boundary conditions to reduce the differences between the results. It is demonstrated that the ambient vibration measurements are enough to identify the most significant modes of highway bridges. After finite element model updating, maximum differences between the natural frequencies are reduced averagely from 23% to 3%. The updated finite element model reflects the dynamic characteristics of the bridge better, and it can be used to predict the dynamic response under complex external forces. It is also helpful for further damage identification and health condition monitoring. Analytical model of the bridge before and after model updating is analyzed using 1992 Erzincan earthquake record to determine the seismic behaviour. It can be seen from the analysis results that displacements increase by the height of bridge columns and along to middle point of the deck and main arches. Bending moments have an increasing trend along to first and last 50 m and have a decreasing trend long to the middle of the main arches.

• Smart Structures and Systems
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• v.33 no.2
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• pp.145-163
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• 2024

The evaluation of dynamic characteristics of bridges under operational traffic loads is a crucial aspect of bridge structural health monitoring. In the vehicle-bridge interaction (VBI) system, the vibration responses of bridge exhibit time-varying characteristics. To address this issue, an accurate time-frequency analysis method that combines the autoregressive power spectrum based empirical wavelet transform (AR-EWT) and local maximum synchrosqueezing transform (LMSST) is proposed to identify the time-varying instantaneous frequencies (IFs) of the bridge in the VBI system. The AR-EWT method decomposes the vibration response of the bridge into mono-component signals. Then, LMSST is employed to identify the IFs of each mono-component signal. The AR-EWT combined with the LMSST method (AR-EWT+LMSST) can resolve the problem that LMSST cannot effectively identify the multi-component signals with weak amplitude components. The proposed AR-EWT+LMSST method is compared with some advanced time-frequency analysis techniques such as synchrosqueezing transform (SST), synchroextracting transform (SET), and LMSST. The results demonstrate that the proposed AR-EWT+LMSST method can improve the accuracy of identified IFs. The effectiveness and applicability of the proposed method are validated through a multi-component signal, a VBI numerical model with a four-degree-of-freedom half-car, and a VBI model experiment. The effect of vehicle characteristics, vehicle speed, and road surface roughness on the identified IFs of bridge are investigated.

• Journal of Korean Tunnelling and Underground Space Association
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• v.5 no.4
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• pp.401-409
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• 2003

Recently, the development of underground structures is to be inevitably necessary due to the increase in population and traffic volume that has caused to the limit of urban land use and the heavy traffic jams. Therefore, underground structures such as subway, underground shopping centers, lifeline facilities and so on, have been increasingly constructed, On the other hand, several social problems have occurred during construction, i.e., ground subsidence, noise, and vibration. Therefore, safer and more beneficial methods for underground construction are on the demand. In this research, N.T.R.(New Tubular Roof) method has been modified and utilized for solving those problems and overcoming the difficulties connected with the bored tunnel construction of large underground openings in unfavorable ground, often under the water table, and with overburdens that are too shallow to solve problems of stability using traditional methods. The N.T.R. method has been modified to suit for Korean geotechnical conditions, and was made up for the weak points-the water leakage from walls and tops, the maintenance and the lack of stability-of the conventional methods. This paper dealt with the features and the applicability of N.T.R. Method based on the results from numerical analysis and data from in-situ monitoring system.