Précédent|Prochain

InSAR deformation data decomposition and information analysis of Jiaozhou bay bridge, Qingdao

  • role： First author第一作者
  • Affiliation：

    School of Government, Peking University, Beijing 100101， China

  • Email：zhumaowork@126.com
  • Introduction：朱茂，1988年生,男,博士研究生,研究方向为InSAR形变测量技术、InSAR应用分析。E-mail: zhumaowork@126.com
ZHU Mao1,  
  • role： Corresponding author通信作者
  • Affiliation：

    School of Government, Peking University, Beijing 100101， China

  • Email：tyshen@pku.edu.cn
  • Introduction：沈体雁，1971年生,男,教授,研究方向为城市风险评估和综合治理。E-mail: tyshen@pku.edu.cn
SHEN Tiyan1*,  
  • Affiliation：

    Qingdao Geotechnical Investigation & Surveying Research Institute, Qingdao 266032, China

LYU Fenghua2,  
  • Affiliation：

    Beijing Vastitude Technology Co., Ltd, Beijing100081, China

GE Chunqing3,  
  • Affiliation：

    Beijing Vastitude Technology Co., Ltd, Beijing100081, China

BAI Shujian3,  
  • Affiliation：

    Beijing Vastitude Technology Co., Ltd, Beijing100081, China

JIA Zhihui3,  
  • Affiliation：

    Beijing Vastitude Technology Co., Ltd, Beijing100081, China

WANG Dawei3

résumé

The study selected Qingdao Jiaozhou Bay Bridge as the study object and gathered information on deep mining based on InSAR deformation data acquired from Jan 2014 to May 2016.Two new deformation models with seasonal variation and temperature variation were first introduced in data analysis. These two models and the traditional linear model were utilized to decompose the deformation evolution data. Thereafter, the performance of the different models was evaluated by calculating the deviation component among the three models and the measured data. After analyzing the data of a section of the bridge, the deformation information along the longitudinal direction was acquired. The deformation characteristics of the PS points on both sides of the expansion joint and bridge structure were discussed.Results were used to confirm that the periodic deformation component was the main deformation component on the bridge, thus validating the performance of the Linear–Periodical model as the best among the models. Meanwhile, the thermal effect of the bridge panels caused the difference in the deformation between the two sides of the expansion joint.The analysis of measured data confirms that InSAR technology has the capacity to monitor the microdeformation information of the bridge. In the future, it can identify the bridge with deformation risk early, and search the bridge with risk and its corresponding area in advance. At the same time, the measurement data could also be used for risk cause analysis. Finally, it can provide technical support for urban bridge risk management.

mots-clés

deformation monitoring;InSAR;bridge deformation analysis;Jiaozhou bay bridge;deformation decomposition;information analysis

References

  1. 1.
    Bamler R and Hartl P. 1998. Synthetic aperture radar interferometry. Inverse Problems, 14(4): R1-R54
  2. 2.
    Costantini M, Falco S, Malvarosa F, Minati F, Trillo F and Vecchioli F. 2014. Persistent scatterer pair interferometry: approach and application to COSMO-SkyMed SAR data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(7): 2869-2879
  3. 3.
    Covello F, Battazza F, Coletta A, Lopinto E, Fiorentino C, Pietranera L, Valentini G and Zoffoli S. 2010. COSMO-SkyMed an existing opportunity for observing the Earth. Journal of Geodynamics, 49(3/4): 171-180
  4. 4.
    Ferretti A, Prati C and Rocca F. 1999. Non-uniform motion monitoring using the permanent scatterers technique//Proceedings of the Second International Workshop on ERS SAR Interferometry. Liege, Belgium: ESA: 1-6
  5. 5.
    Ferretti A, Prati C and Rocca F. 2000. Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 38(5): 2202-2212
  6. 6.
    Ferretti A, Prati C and Rocca F. 2001. Permanent scatterers in SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 39(1): 8-20
  7. 7.
    Fornaro G, Reale D and Verde S. 2013. Bridge thermal dilation monitoring with millimeter sensitivity via multidimensional SAR imaging. IEEE Geoscience and Remote Sensing Letters, 10(4): 677-681
  8. 8.
    Huang Q H, Ding Y L, Wang Y A and Yin F Z. 2017. InSAR-based longitudinal displacement monitoring and analysis on Nanjing Dashengguan bridge. Journal of Southeast University (Natural Science Edition), 47(3): 584-589
  9. 9.
    Lazecky M, Hlavacova I, Bakon M, Sousa J J, Perissin D and Patricio G. 2017. Bridge displacements monitoring using space-borne X-band SAR interferometry. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(1): 205-210
  10. 10.
    Lazecký M, Rapant P, Perissin D and Bakoň M. 2014. Deformations of highway over undermined ostrava-svinov area monitored by InSAR using limited Set of SAR images. Procedia Technology, 16: 414-421
  11. 11.
    Liao M S and Wang T. 2014. Time Series InSAR Technology and Its Application. Beijing: Science Press
  12. 12.
    Massonnet D and Feigl K L. 1998. Radar interferometry and its application to changes in the Earth’s surface. Reviews of Geophysics, 36(4): 441-500
  13. 13.
    Massonnet D, Rossi M, Carmona C, Adragna F, Peltzer G, Feigl K and Rabaute T. 1993. The displacement field of the Landers earthquake mapped by radar interferometry. Nature, 364(6433): 138-142
  14. 14.
    Qin X Q, Yang M S, Wang H M, Yang T L, Lin J X and Liao M S. 2016. Application of high-resolution PS-InSAR in deformation characteristics probe of urban rail transit. Acta Geodaetica et Cartographica Sinica, 45(6): 713-721
  15. 15.
    Su X Z, Su X and Yang X M. 2004. Application of GPS in monitoring deformation of large scaled bridge. Journal of Railway Engineering Society, (1):77-79
  16. 16.
    Wang D and Yang S B. 2016. Discussion on bridge deformation monitoring technology. Geospatial Information, 14(6): 72-74, 88
  17. 17.
    Yao L B, Yao P, Wang R P and Meng X L. 2008. GPS-based dynamic monitoring and analysis of Nanpu bridge deformation. Journal of Tongji University (Natural Science), 36(12): 1633-1636, 1664
  18. 18.
    Zebker H A, Rosen P A, Goldstein R M, Gabriel A and Werner C L. 1994. On the derivation of coseismic displacement fields using differential radar interferometry: the Landers earthquake. Journal of Geophysical Research: Solid Earth, 99(B10): 19617-19634
  19. 19.
    Zhao J W, Wu J C, Ding X L and Wang M Z. 2017. Elevation extraction and deformation monitoring by multitemporal InSAR of Lupu bridge in Shanghai. Remote Sensing, 9(9): 897
  20. 20.
    Zhu J J, Li Z W and Hu J. 2017. Research progress and methods of InSAR for deformation monitoring. Acta Geodaetica et Cartographica Sinica, 46(10): 1717-1733

Lire l'article complet

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website