Traffic Volume Dependent Displacement Estimation Model for Gwangan Bridge Using Monitoring Big Data

교량 모니터링 빅데이터를 이용한 광안대교의 교통량 의존 변위 추정 모델

  • Received : 2017.08.30
  • Accepted : 2018.01.12
  • Published : 2018.04.01


In this study a traffic volume dependent displacement estimation model for Gwangan Bridge was developed using bridge monitoring big data. Traffic volume data for four different vehicle types and the vertical displacement data in the central position of the Gwangan Bridge were used to develop and validate the estimation model. Two statistical estimation models were developed using multiple regression analysis (MRA) and principal component analysis (PCA). Estimation performance of those two models were compared with actual values. The results show that both the MRA and the PCA based models are successfully estimating the vertical displacement of Gwangan Bridge. Based on the results, it is concluded that the developed model can effectively be used to predict the traffic volume dependent displacement behavior of Gwangan Bridge.


  1. Bae, D. B. and Hwang, E. S. (2004). "Fatigue load model for the design of steel bridges." Journal of the Korean Society of Civil Engineers, Vol. 24, No. 1A, pp. 225-232 (in Korean).
  2. Chang, S. J. and Kim, N. S. (2010). "Applications of displacement response estimation algorithm using mode decomposition technique to existing bridges." Journal of the Korean Society of Civil Engineers, Vol. 30, No. 3A, pp. 257-264 (in Korean).
  3. Chi, S. H. (2016). "Big data analysis of unstructured documents and video images in the construction industry." Magazine of Korean Society of Civil Engineers, Vol. 64, No. 8, pp. 15-18 (in Korean).
  4. Gonzalez, A. (2010). Development of a Bridge Weigh-In-Motion System: A Technology to Convert the Bridge Response to the Passage of Traffic Into Data on Vehicle Configurations, Speeds, Times of Travel and Weights, Lambert Academic Publishing.
  5. Kaiser, H. F. (1974). "An index of factorial simplicity." Psychometrika, Vol. 39, No. 1, pp. 31-36.
  6. Kim, H. J., Yoon, J. G., Lee, J. H. and Chang, S. P. (2005). "Analysis of long-term monitoring results of a Cable-Stayed Bridge using ARX model." Proceedings of KSCE 2005 Annual Conference, pp. 928-931 (in Korean).
  7. Oh, S. H. (2009). "An analysis of noise robustness for multilayer perceptrons and its improvements." Journal of the Korea Contents Association, Vol. 9, No. 1, pp. 159-166 (in Korean).
  8. Park, J. C. (2015). "Evaluation of thermal movements of a Cable- Stayed Bridge using temperatures and displacements data." Journal of the Korean Society of Civil Engineers, Vol. 35, No. 4, pp. 779-789 (in Korean).
  9. Park, J. C., Park, C. M. and Song, P. Y. (2004). "Evaluation of structural behaviors using full scale measurements on the Seo Hae Cable-Stayed Bridge." Journal of the Korean Society of Civil Engineers, Vol. 24, No. 2A, pp. 249-257 (in Korean).
  10. Park, J. H. (2015). The Optimum Design of Expansion Joints by Long-Term Monitoring Data for the Diamond Bridge, Master Thesis, Pukyong National University (in Korean).
  11. Park, J. H. and Kim, S. Y. (2017). "Analysis of suspension bridge reinforced truss strain by traffic." 2017 Proceedings of KSMI Annual Conference, pp. 357-358 (in Korean).
  12. Park, J. S., Ro, S. K., Park, J. H., Nam, S. S. and Moon, D. J. (2013). "Correlation analysis between deflection and temperature in suspension bridge using GNSS and laser displacement sensor." Proceedings of KSMI 2013 Spring Conference, pp. 375-379 (in Korean).
  13. Song, J. J. (2016). SPSS/AMOS Statistical Analysis Method for Paper Writing, 21C Book Inc., Korea (in Korean).
  14. Sousa, H., Zavitsas, K., Polak, J. and Chryssanthopoulos, M. (2014). "Inferring asset live load distributions from traffic flow data: a new SHM opportunity?" EWSHM-7th European Workshop on Structural Health Monitoring., Nantes, France, pp. 435-442.
  15. Won, T. Y. and Jeong, S. W. (2015). Statistical Analysis - SPSS 18.0, Hannarae Book Inc., Korea (in Korean).
  16. Yang, Y. B., Yau, J. D. and Wu, Y. S. (2004). Vehicle-Bridge Interaction Dynamics, World Scientific Publishing Co., New Jersey, USA.
  17. Zhou, Y. and Chen, S. (2017). Dynamic Assessment of Bridge Deck Performance Considering Realistic Bridge-Traffic Interaction, No. MPC 17-333, North Dakota State University - Upper Great Plains Transportation Institute, Fargo: Mountain-Plains Consortium, North Dakota, USA.