Tạp chí
 
Năm 2020
 
Số 61, Kỳ 6, [12 - 2020] - Tiếng Anh

Application of correlation and regression analysis between GPS - RTK and environmental data in processing the monitoring data of cable - stayed

DOI:10.46326/JMES.2020.61(6).07

  • Cơ quan:

    1 Faculty of Geomatics and Land Administration, Hanoi University of Mining and Geology, Vietnam
    2 University of Transport and Communications, Hanoi, Vietnam
    3 The branch of Hanoi University of Natural Resources and Environment in Thanh Hoa Province, Vietnam

  • *Tác giả liên hệ:
    This email address is being protected from spambots. You need JavaScript enabled to view it.
  • Nhận bài: 28-09-2020
  • Sửa xong: 29-11-2020
  • Chấp nhận: 31-12-2020
  • Ngày đăng: 31-12-2020
Trang: 59 - 72
Lượt xem: 2729
Xem onlineXem online
Lượt tải: 930
Tải về PDF
★★★★★Yêu thích: 1.0, Số lượt: 92
  • ★
  • ★
  • ★
  • ★
  • ★
Bạn yêu thích

Trích dẫn: 1

Tóm tắt:

Structural Health Monitoring system - SHMs has been playing a vital role in monitoring large - scale structures during their performance in a lifetime, especially with the long - span bridge, such as a suspended bridge or cable - stayed bridge. In a SHM system, many kinds of sensors are used to set up at the specific locations in order to monitor and detect any changes of structures in real - time based on the changes of monitoring data as well as the changes of correlation among monitoring data types. This paper proposes a method of applying the correlation and regression analysis for processing the displacement monitoring data acquired by GPS - RTK considering the effects of environmental factors such as temperature and wind - speed. The results show that the air - temperature has high correlation with the displacements of a cable - stayed bridge acquired by GPS - RTK measurement along to specific directions while the wind - speed has low correlation. Then the general displacement of the target bridge could be recognized and regression equation is also built to predict the bridge displacement under effects of the air temperature.

Trích dẫn
Tinh Duc Le, Hien Van Le, Linh Thuy Nguyen, Thanh Kim Thi Nguyen và Duy Tien Le, 2020. Application of correlation and regression analysis between GPS - RTK and environmental data in processing the monitoring data of cable - stayed, Tạp chí Khoa học kỹ thuật Mỏ - Địa chất, số 61, kỳ 6, tr. 59-72.
Tài liệu tham khảo

Cao Van Nguyen et al., (2002). Theory of probability and mathematical statistics. Publisher of education, Hanoi.

Celebi, M., (2000). GPS in dynamic monitoring of long - period structures. Soil Dynamics and Earthquake Engineering, 20(5), 477 - 483.

Cheng, P., John, W., and Zheng, W., (2002). Large structure health dynamic monitoring using GPS technology. In FIG XXII International Congress, Washington, DC USA.

Cornwell, P., Farrar, C. R., Doebling, S. W., and Sohn, H., (1999). Environmental variability of modal properties. Experimental Techniques, 23(6), 45 - 48.

Duc Tinh Le, (2012). Application of statistical methods in analyzing the deformation of hydropower projects in Vietnam. Final report of topic for supporting PhD student, code number N2010 - 31.

Farrar C. R., Cornwell P., Doebling S. W., and Prime M. B., (2000). Structural Health Monitoring Studies of the Alamosa Canyon and I - 40 Bridges. Los Alamos National Laboratory, LA - 13635 - MS.

Fujino, Y., Murata, M., Okano, S., and Takeguchi, M., (2000). Monitoring system of the Akashi Kaikyo Bridge and displacement measurement using GPS. In SPIE's 5th Annual International Symposium on Nondestructive Evaluation and Health Monitoring of Aging Infrastructure (pp. 229 - 236). International Society for Optics and Photonics. 

H. V. Le, M. Nishio, H. Yamada, H. Katsuchi, (2015). Statistical condition assessment of a cable stayed bridge using GPS structural health monitoring data. The 7th International Conference of Structural Health Monitoring of Intelligent Infrastructure SHMII, Italy.

Hien V. Le, Mayuko Nishio, (2015). Time - series analysis of GPS monitoring data from a long - span bridge considering the global deformation due to air temperature changes. Journal of Civil Structural Health Monitoring, Springer 5, 415 - 425.

Kaloop, M. R., and Li, H., (2009). Monitoring of bridge deformation using GPS technique. KSCE Journal of Civil Engineering, 13(6), 423 - 431.

Kaloop, M. R., and Li, H., (2011). Sensitivity and analysis GPS signals based bridge damage using GPS observations and wavelet transform. Measurement, 44(5), 927 - 937 .

Khanh Tran, Tinh Duc Le, (2010). Application of correlation analysis method in assessing the structural displacement. Journal of science and technique of mining and geology (31). 

Khanh Tran, Phuc Quang Nguyen. (2010). Structural Deformation and Displacment Monitoring. Publisher of Transportation.

Omenzetter P., and Brownjohn J. M. W., (2005). A seasonal ARIMAX time series model for strain - temperature relationship in an instrumented bridge. Proceedings of the 5th International Workshop on Structural Health Monitoring, 299 - 306. 

Omenzetter, P., and Brownjohn, J. M. W., (2006). Application of time series analysis for bridge monitoring. Smart Materials and Structures, 15(1), 129 - 138.

Peter J. Rousseeuw, Annick M. Leroy, (198)7. Robust Regression and Outlier Detection. Book, Wiley - Interscience.

Sanford Weisberg, (2005). Applied Linear Regression. Book, third edition. Wiley - Interscience.

Shumway, R. H., Stoffer, D. S., (2010). Time series analysis and its applications: with R examples. Springer.

Sohn, H., Czarnecki, J. A., Farrar, C. R., (2000). Structural health monitoring using statistical process control. Journal of Structural Engineering, 126(11), 1356 - 1363.

Sohn, H., Dzwonczyk, M., Straser, E. G., Kiremidjian, A. S., Law, K. H., and Meng, T., (1999). An experimental study of temperature effect on modal parameters of the Alamosa Canyon Bridge. Earthquake engineering and structural dynamics, 28(8), 879 - 897.

Các bài báo khác