• Title/Summary/Keyword: Bridge monitoring data

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The Development of Measuring, Monitoring and Control System for Large Bridge Using Ubiquitous Computing Technology (유비쿼터스 컴퓨팅 기술을 활용한 대형교량의 계측, 모니터링, 통제시스템)

  • Lee Seung-Jae;Lim Jong-Kwon;Min Dae-Hong;Hwang Kyung-Hun
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • 2004.11a
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    • pp.182-187
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    • 2004
  • Recently the application area of wireless LAN has been increased, rapidly. The application area was limited in indoor, but as the data throughput and performance of wireless LAN becomes better the application is to extend to the Internet connection and wireless(Ubiqitous) bridge in outdoor. In this paper, In this paper, the data throughput of wireless LAN in mobile environment is measured, and the usability of wireless LAN for develop bridge health monitoring system is confirmed.

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Structural evaluation of all-GFRP cable-stayed footbridge after 20 years of service life

  • Gorski, Piotr;Stankiewicz, Beata;Tatara, Marcin
    • Steel and Composite Structures
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    • v.29 no.4
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    • pp.527-544
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    • 2018
  • The paper presents the study on a change in modal parameters and structural stiffness of cable-stayed Fiberline Bridge made entirely of Glass Fiber Reinforced Polymer (GFRP) composite used for 20 years in the fjord area of Kolding, Denmark. Due to this specific location the bridge structure was subjected to natural aging in harsh environmental conditions. The flexural properties of the pultruded GFRP profiles acquired from the analyzed footbridge in 1997 and 2012 were determined through three-point bending tests. It was found that the Young's modulus increased by approximately 9%. Moreover, the influence of the temperature on the storage and loss modulus of GFRP material acquired from the Fiberline Bridge was studied by the dynamic mechanical analysis. The good thermal stability in potential real temperatures was found. The natural vibration frequencies and mode shapes of the bridge for its original state were evaluated through the application of the Finite Element (FE) method. The initial FE model was created using the real geometrical and material data obtained from both the design data and flexural test results performed in 1997 for the intact composite GFRP material. Full scale experimental investigations of the free-decay response under human jumping for the experimental state were carried out applying accelerometers. Seven natural frequencies, corresponding mode shapes and damping ratios were identified. The numerical and experimental results were compared. Based on the difference in the fundamental natural frequency it was again confirmed that the structural stiffness of the bridge increased by about 9% after 20 years of service life. Data collected from this study were used to validate the assumed FE model. It can be concluded that the updated FE model accurately reproduces the dynamic behavior of the bridge and can be used as a proper baseline model for the long-term monitoring to evaluate the overall structural response under service loads. The obtained results provided a relevant data for the structural health monitoring of all-GFRP bridge.

Behavior Character Analysis of Super Long Suspension Bridge using GNSS (GNSS를 활용한 초장대 현수교의 거동 특성 분석)

  • Park, Je-Sung;Hong, Seunghwan;Kim, Mi-Kyeong;Kim, Tai-Hoon;Sohn, Hong-Gyoo
    • Korean Journal of Remote Sensing
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    • v.35 no.5_2
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    • pp.831-840
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    • 2019
  • Recently, the span length of long-span bridges is getting longer. As a result, it has been suggested that a new concept called 'super long-span bridge'. In case of super long span bridges, the structure is being complicated and the importance of structural stability is being emphasized. However, until recently, the most commonly used sensors (dual axis clinometer, anemometer, strain gauge, etc.) have got limit about the bridge monitoring. Consequently, we researched the application of a Global Navigation Satellite System (GNSS) to improve the limit of the existing sensors. In this study, the dual axis clinometer, the anemometer and the strain gauge together with the GNSS were used to analyze the behavior of a super-long suspension bridge. Also, we propose the detailed method of bridge monitoring using the GNSS. This study consisted of three steps. First step calculated the absolute coordinates of the towers and the longitudinal axis direction of the study bridge using the GNSS. In second step, through the analysis of the long-term behavior in shortly after construction, we calculated the permanent displacement and evaluated the stability of main towers. Third step analyzed the behavior of bridge by the wind direction and was numerically indicated. Consequently, the bridge measurement using the GNSS appeared that the acquired data is able to easy processing according to the analysis purpose. If we will use together the existing measurement sensors with the GNSS on the maintenance of the super long-span bridge, we figure each error of measurement data and improve the monitoring system through calibration. As a result, we acquire the accurate displacement of bridge and figure the behavior of bridge. Consequently, we identified that it is able to construct the effective monitoring system.

Application of Differential GPS for the Displacement Measurement of Self-anchored Suspension Bridge under the Static and Dynamic Loading Cases (DGPS 기법을 이용한 자정식 현수교의 정동적 변위응답 측정 및 분석)

  • Kim, Hyung-Tae;Seo, Ju-Won
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.19 no.11
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    • pp.1126-1132
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    • 2009
  • Bridge structures are designed to support ordinary loadings such as vehicles, wind, temperature and current as well as unexpected loadings like earthquakes and storm. Especially, the displacement of Flexible bridges like an suspension bridge under ordinary loading conditions is necessary to be monitored. In case of long span bridges, there are some difficulties in monitoring the displacement of center of the main span using traditional laser displacement sensors. In this study, the static and dynamic displacement responses due to vehicle loadings were measured by DGPS(differential global positioning system) technique. The displacement response data were compared with data obtained from traditional laser displacement sensors so that the static and dynamic behavior of the bridge under vehicle loadings was examined and the applicability of the displacement response measurement using DGPS technique was verified. The static and dynamic loading test for an self-anchored suspension bridge, So-rok Bridge, was performed using vehicles. The displacement response from DGPS technique and that from laser displacement sensors of the bridge monitoring system were compared. The amplitude of white noise from DGPS based measurement was about 7 mm and that of laser displacement sensor based measurement was about 3 mm. On the other hand, dynamic behavior of the center of main span from DGPS based measurement showed better agreement with influence line of the bridge than that from laser displacement sensors. In addition, there were some irregular and discontinuous variation of data due to the instability of GPS receivers or frequent appearance of GPS satellites. Post-processing via the reference station close to an observation post provided by NGII(National Geographic Information Institute) will be a counter-plan for these defects.

Damage detection of bridges based on spectral sub-band features and hybrid modeling of PCA and KPCA methods

  • Bisheh, Hossein Babajanian;Amiri, Gholamreza Ghodrati
    • Structural Monitoring and Maintenance
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    • v.9 no.2
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    • pp.179-200
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    • 2022
  • This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T2 and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.

Automated data interpretation for practical bridge identification

  • Zhang, J.;Moon, F.L.;Sato, T.
    • Structural Engineering and Mechanics
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    • v.46 no.3
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    • pp.433-445
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    • 2013
  • Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.

SHM-based probabilistic representation of wind properties: statistical analysis and bivariate modeling

  • Ye, X.W.;Yuan, L.;Xi, P.S.;Liu, H.
    • Smart Structures and Systems
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    • v.21 no.5
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    • pp.591-600
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    • 2018
  • The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

Periodic seismic performance evaluation of highway bridges using structural health monitoring system

  • Yi, Jin-Hak;Kim, Dookie;Feng, Maria Q.
    • Structural Engineering and Mechanics
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    • v.31 no.5
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    • pp.527-544
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    • 2009
  • In this study, the periodic seismic performance evaluation scheme is proposed using a structural health monitoring system in terms of seismic fragility. An instrumented highway bridge is used to demonstrate the evaluation procedure involving (1) measuring ambient vibration of a bridge under general vehicle loadings, (2) identifying modal parameters from the measured acceleration data by applying output-only modal identification method, (3) updating a preliminary finite element model (obtained from structural design drawings) with the identified modal parameters using real-coded genetic algorithm, (4) analyzing nonlinear response time histories of the structure under earthquake excitations, and finally (5) developing fragility curves represented by a log-normal distribution function using maximum likelihood estimation. It is found that the seismic fragility of a highway bridge can be updated using extracted modal parameters and can also be monitored further by utilizing the instrumented structural health monitoring system.

Development of Vibration Powered Generator for Vibration Monitoring (진동모니터링을 위한 자가진동발전기의 개발)

  • 김재민;최남섭
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.05a
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    • pp.434-441
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    • 2003
  • This paper presents a generator for stand-alone vibration monitoring system of bridge structure based on ambient vibration of bridge. In this paper, a novel electric power generator which has minimum effect of armature reaction is proposed. The related mechanical and electrical design equations are obtained and a pilot generator has been implemented. In addition, the charging system for extremely low generator current is discussed, and some improvements are identified for the system. This investigation reveals that diode characteristics of rectifier is dominant factor in the charging process. Finally, both the simulation, which uses real measurement data of the Namhae bridge as input of the pilot generator, and indoor test are carried out. The results showed the applicability and effectiveness of the stand-alone vibration powered generator.

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Automatic modal identification and variability in measured modal vectors of a cable-stayed bridge

  • Ni, Y.Q.;Fan, K.Q.;Zheng, G.;Ko, J.M.
    • Structural Engineering and Mechanics
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    • v.19 no.2
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    • pp.123-139
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    • 2005
  • An automatic modal identification program is developed for continuous extraction of modal parameters of three cable-supported bridges in Hong Kong which are instrumented with a long-term monitoring system. The program employs the Complex Modal Indication Function (CMIF) algorithm for identifying modal properties from continuous ambient vibration measurements in an on-line manner. By using the LabVIEW graphical programming language, the software realizes the algorithm in Virtual Instrument (VI) style. The applicability and implementation issues of the developed software are demonstrated by using one-year measurement data acquired from 67 channels of accelerometers permanently installed on the cable-stayed Ting Kau Bridge. With the continuously identified results, variability in modal vectors due to varying environmental conditions and measurement errors is observed. Such an observation is very helpful for selection of appropriate measured modal vectors for structural health monitoring use.