• Smart Structures and Systems
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• v.12 no.3_4
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• pp.251-269
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• 2013

Measurement of deflections of certain bridges is usually hampered by corruption of the GPS signal by multipath associated with passing vehicles, resulting to unrealistically large apparent displacements. Field data from the Gorgopotamos train bridge in Greece and systematic experiments revealed that such bias is due to superimposition of two major effects, (i) changes in the geometry of satellites because of partial masking of certain satellites by the passing vehicles (this effect can be faced with solutions excluding satellites that get temporarily blocked by passing vehicles) and (ii) dynamic multipath caused from reflection of satellite signals on the passing trains, a high frequency multipath effect, different from the static multipath. Dynamic multipath seems to have rather irregular amplitude, depending on the geometry of measured satellites, but a typical pattern, mainly consisting of a baseline offset, wide base peaks correlating with the sequence of main reflective surfaces of the vehicles passing next to the antenna. In cases of limited corruption of GPS signal by dynamic multipath, corresponding to scale distortion of the short-period component of the GPS waveforms, we propose an algorithm which permits to reconstruct the waveform of bridge deflections using a weak fusion of GPS and RTS data, based on the complementary characteristics of the two instruments. By application of the proposed algorithm we managed to extract semi-static and dynamic displacements and oscillation frequencies of a historical railway bridge under train loading by using noisy GPS and RTS recordings. The combination of GPS and RTS is possible because these two sensors can be fully collocated and have complementary characteristics, with RTS and GPS focusing on the long- and short-period characteristics of the displacement, respectively.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.3
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• pp.219-227
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• 2016

In this study, we have proposed a method of monitoring of bridges under construction in view of the long-term behavior of the prestress concrete bridge of which the Free Cantilever Method is applied. As a method to confirm the ability of the long-term behavior of the concrete box girder, temperature sensors and strain gauges were installed, and the measured data was used to calculate creep coefficient. Moreover, we have measured the stress of the concrete box girder during construction which was applied with creep coefficient and compared with the changes in temperature to analyze the vertical displacement along the segment. In conclusion, monitoring of the FCM bridge during construction in consideration of the long-term behavior can be analyzed efficiently by suing temperature and displacement data without the use of laser displacement meter or laser delfectometer.

• Wind and Structures
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• v.25 no.2
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• pp.195-214
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• 2017

Full-scale wind characteristics based on the field measurements is an essential element in structural wind engineering. Statistical analysis of the wind characteristics at Sutong Cable-stayed Bridge (SCB) site is conducted in this study with the recorded long-term wind data from structural health monitoring system (SHMS) between 2008 and 2015. Both the mean and turbulent wind characteristics and power spectra are comprehensively investigated and compared with those in the current codes of practice, such as the measured wind rose diagram, monthly maximum mean wind speed, turbulence intensity, integral length scale. Measurement results based on the monitoring data show that winds surrounding the SCB site are substantially influenced by the southeast monsoon in summer and strong northern wind in winter. The measured turbulence intensity is slightly higher than the recommended values in specifications, while the measured ratio of lateral to longitudinal turbulence intensity is slightly lower. An approximately linear relationship between the measured turbulence intensities and gust factors is obtained. The mean value of the turbulence integral length scale is smaller than that of typical typhoon events. In addition, it is found that the Kaimal spectrum is suitable to be adopted as the power spectrum for longitudinal wind component at the SCB site. This contribution would provide important wind characteristic references for the wind performance evaluation of SCB and other civil infrastructures in adjacent regions.

• Smart Structures and Systems
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• v.29 no.1
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• pp.93-103
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• 2022

With the wider availability of sensor technology through easily affordable sensor devices, several Structural Health Monitoring (SHM) systems are deployed to monitor vital civil infrastructure. The continuous monitoring provides valuable information about the health of the structure that can help provide a decision support system for retrofits and other structural modifications. However, when the sensors are exposed to harsh environmental conditions, the data measured by the SHM systems tend to be affected by multiple anomalies caused by faulty or broken sensors. Given a deluge of high-dimensional data collected continuously over time, research into using machine learning methods to detect anomalies are a topic of great interest to the SHM community. This paper contributes to this effort by proposing a relatively new time series representation named "Shapelet Transform" in combination with a Random Forest classifier to autonomously identify anomalies in SHM data. The shapelet transform is a unique time series representation based solely on the shape of the time series data. Considering the individual characteristics unique to every anomaly, the application of this transform yields a new shape-based feature representation that can be combined with any standard machine learning algorithm to detect anomalous data with no manual intervention. For the present study, the anomaly detection framework consists of three steps: identifying unique shapes from anomalous data, using these shapes to transform the SHM data into a local-shape space and training machine learning algorithms on this transformed data to identify anomalies. The efficacy of this method is demonstrated by the identification of anomalies in acceleration data from an SHM system installed on a long-span bridge in China. The results show that multiple data anomalies in SHM data can be automatically detected with high accuracy using the proposed method.

• Wind and Structures
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• v.17 no.1
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• pp.43-68
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• 2013

The fluctuating wind induced vibration is one of the most important factors which has been taken into account in the design of long-span bridge due to the low stiffness and low natural frequency. Field measurement characteristics of sustained wind on structure site can provide accurate wind load parameters for wind field simulation and structural wind resistance design. As a suspension bridge with 1490 m main span, the Runyang Suspension Bridge (RSB) has high sensitivity to fluctuating wind. The simultaneous and continuously wind environment field measurement both in mid-span and on tower top is executed from 2005 up to now by the structural health monitoring system installed on this bridge. Based on the recorded data, the wind characteristic parameters, including mean wind speed, wind direction, the turbulence intensity, the gust factors, the turbulence integral length, power spectrum and spatial correlation, are analyzed in detail and the coherence functions of those parameters are evaluated using statistical method in this paper. The results indicate that, the turbulence component of sustain wind is larger than extremely strong winds although its mean wind speed is smaller; the correlation between turbulence parameters is obvious; the power spectrum is special and not accord with the Simiu spectrum and von Karman spectrum. Results obtained in this study can be used to evaluate the long term reliability of the Runyang Suspension Bridge and provide reference values for wind resistant design of other structures in this region.

• Smart Structures and Systems
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• v.10 no.3
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• pp.209-228
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• 2012

Structural health monitoring with wireless sensor networks has received much attention in recent years due to the ease of sensor installation and low deployment and maintenance costs. However, sensor network technology needs to solve numerous challenges in order to substitute conventional systems: large amounts of data, remote configuration of measurement parameters, on-site calibration of sensors and robust networking functionality for long-term deployments. We present a structural health monitoring network that addresses these challenges and is used in several deployments for monitoring of bridges and buildings. Our system supports a diverse set of sensors, a library of highly optimized processing algorithms and a lightweight solution to support a wide range of network runtime configurations. This allows flexible partitioning of the application between the sensor network and the backend software. We present an analysis of this partitioning and evaluate the performance of our system in three experimental network deployments on civil structures.

• Journal of the Korea institute for structural maintenance and inspection
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• v.9 no.3
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• pp.129-138
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• 2005

This paper presents a methodology for the determination of optimal managing criteria for cable tension force in cable-stayed bridges using acceleration data acquired by monitoring system. There are many long span bridges installed with monitoring system in Korea. The monitoring systems are installed to diagnose abnormal behavior or damages in bridges and to warn these to bridge management agency. In cable-stayed bridges, the cable tension force could be an important indicator of abnormal behavior because of the geometric configuration of the cable-stayed bridge. If the management value of cable tension force is set too high or too low, then the monitoring system could not warn properly for the abnormal behavior of a bridge. Generally, the management value is set by empirical or engineering judgment, but in this paper, a new methodology for the determination of managing criteria for cable tension force is proposed based on the probability distribution model for tension force and reliability analysis. The proposed methodology is applied to a real concrete cable-stayed bridge in order to investigate its applicability.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1107-1127
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• 2016

Studies on dynamic characteristics of the hanger vibration using field monitoring data are important for the design and evaluation of high-speed railway truss arch bridges. This paper presents an analysis of the hanger's dynamic displacement responses based on field monitoring of Dashengguan Yangtze River Bridge, which is a high-speed railway truss arch bridge with the longest span throughout the world. The three vibration parameters, i.e., dynamic displacement amplitude, dynamic load factor and vibration amplitude, are selected to investigate the hanger's vibration characteristics in each railway load case including the probability statistical characteristics and coupled vibration characteristics. The influences of carriageway and carriage number on the hanger's vibration characteristics are further investigated. The results indicate that: (1) All the eight railway load cases can be successfully identified according to the relationship of responses from strain sensors and accelerometers in the structural health monitoring system. (2) The hanger's three vibration parameters in each load case in the longitudinal and transverse directions have obvious probabilistic characteristics. However, they fall into different distribution functions. (3) There is good correlation between the hanger's longitudinal/transverse dynamic displacement and the main girder's transverse dynamic displacement in each load case, and their relationships are shown in the hysteresis curves. (4) Influences of the carriageway and carriage number on the hanger's three parameters are different in both longitudinal and transverse directions; while the influence on any of the three parameters presents an obvious statistical trend. The present paper lays a good foundation for the further analysis of train-induced hanger vibration and control.

• Structural Engineering and Mechanics
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• v.36 no.2
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• pp.129-147
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• 2010

This study deals with the viability of using a designed geometrical model consists of plane, polar coordinates (PC) and span length in the determination of bridges deformation. The data of a Tianjin Yonghe bridge located in the southern part of China as collected by RTK-DGPS technique and Accelerometer were used in the analysis. Kalman filter and fast Fourier transformation (FFT) analyses were used to determine the frequency. The results indicate that the designed plane and PC geometrical model are easy to calculate the long-time structural deformation monitoring. In addition, the observed frequency using GPS with the rate of 20 Hz doesn't give correction natural frequency of the observation structures.

• Earthquakes and Structures
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• v.22 no.5
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• pp.503-515
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• 2022

This paper presents the development of seismic fragility curves for a precast reinforced concrete bridge instrumented with a structural health monitoring (SHM) system. The bridge is located near an active seismic fault in the Dominican Republic (DR) and provides the only access to several local communities in the aftermath of a potential damaging earthquake; moreover, the sample bridge was designed with outdated building codes and uses structural detailing not adequate for structures in seismic regions. The bridge was instrumented with an SHM system to extract information about its state of structural integrity and estimate its seismic performance. The data obtained from the SHM system is integrated with structural models to develop a set of fragility curves to be used as a quantitative measure of the expected damage; the fragility curves provide an estimate of the probability that the structure will exceed different damage limit states as a function of an earthquake intensity measure. To obtain the fragility curves a digital twin of the bridge is developed combining a computational finite element model and the information extracted from the SHM system. The digital twin is used as a response prediction tool that minimizes modeling uncertainty, significantly improving the predicting capability of the model and the accuracy of the fragility curves. The digital twin was used to perform a nonlinear incremental dynamic analysis (IDA) with selected ground motions that are consistent with the seismic fault and site characteristics. The fragility curves show that for the maximum expected acceleration (with a 2% probability of exceedance in 50 years) the structure has a 62% probability of undergoing extensive damage. This is the first study presenting fragility curves for civil infrastructure in the DR and the proposed methodology can be extended to other structures to support disaster mitigation and post-disaster decision-making strategies.