Wind and Structures

  • 제38권2호
  • /
  • Pages.119-128
  • /
  • 2024
  • /
  • 1226-6116(pISSN)
  • /
  • 1598-6225(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Particle filter approach for extracting the non-linear aerodynamic damping of a cable-stayed bridge subjected to crosswind action

  • 투고 : 2023.03.02
  • 심사 : 2024.01.21
  • 발행 : 2024.02.25
⟨ 이전 논문 다음 논문 ⟩

초록

The aerodynamic damping is an essential factor that can considerably affect the dynamic response of the cable-stayed bridge induced by crosswind load. However, developing an accurate and efficient aerodynamic damping model is crucial for evaluating the crosswind load-induced response on cable-stayed bridges. Therefore, this study proposes a new method for identifying aerodynamic damping of the bridge structures under crosswind load using an extended Kalman filter (EKF) and the particle filter (PF) algorithm. The EKF algorithm is introduced to capture the aerodynamic damping ratio. PF technique is used to select the optimal spectral representation of the noise. The effectiveness and accuracy of the proposed solution were investigated through full-scale vibration measurement data of the crosswind-induced on the bridge's girder. The results show that the proposed solution can generate an efficient and robust estimation. The errors between the target and extracted values are around 0.01mm and 0.003^o, respectively, for the vertical and torsional motion. The relationship between the amplitude and the aerodynamic damping ratio is linear for small reduced wind velocity and nonlinear with the increasing value of the reduced wind velocity. Finally, the results show the influence of the level of noise.

키워드

과제정보

This research was financially supported by School of Civil Engineering, Southwest Jiaotong University.

참고문헌

  1. Bai, J. (1994), "Least squares estimation of a shift in linear processes", J. Time Series Anal., https://doi.org/10.1111/j.1467-9892.1994.tb00204.x.
  2. Berana, J., Ghoshb, S. and Schella, D. (2009), "On least squares estimation for long-memory lattice processes", J. Multivariate Anal., 100(10), 2178-2194. https://doi.org/10.1016/j.jmva.2009.04.007.
  3. Chen, X. (2013), "Estimation of stochastic crosswind response of wind excited tall buildings with nonlinear aerodynamic damping", Eng. Struct., 56, 766-778. https://doi.org/10.1016/j.engstruct.2013.05.044.
  4. Chen, X. (2014), "Analysis of crosswind fatigue of wind-excited structures with nonlinear aerodynamic damping", Eng. Struct., 74, 145-156. https://doi.org/10.1016/j.engstruct.2014.04.049.
  5. Ehsan, F. and Scanlan, R.H. (1990), "Vortex-induced vibrations of flexible bridges", J. Eng. Mech., 116(6), 1392-1411. https://doi.org/10.1061/(ASCE)0733-9399(1990)116:6(1392).
  6. Ehsan, F. and Scanlan, R.H. (1990), "Vortex-induced vibrations of flexible bridges", J. Eng. Mech., 116(6), 1392-1411. https://doi.org/10.1061/(ASCE)0733-9399(1990)116:6(1392).
  7. Hao, W. Chen, X. and Yang, Q. (2019), "Extraction of nonlinear aerodynamic damping of crosswind-excited tall buildings from aeroelastic model tests", J. Eng. Mech., 146(3) https://doi.org/10.1061/(ASCE)EM.1943-7889.0001731.
  8. Junruang, J. and Boonyapinyo, V. (2020), "Vortex induced vibration and flutter instability of two parallel cable-stayed bridges", Wind Struct., 30(6), 633. https://doi.org/10.12989/was.2020.30.6.633.
  9. Lin, Y.H. and Jiao, X.L. (2021), "Adaptive kernel auxiliary particle filter method for degradation state estimation", Reliability Eng. Syst. Safety, 211, 107562. https://doi.org/10.1016/j.ress.2021.107562.
  10. Mashad, M. and Jones, N.P. (2014), "A model for vortex-induced vibration analysis of longspan bridges", J. Wind Eng. Ind. Aerod., 134, 96-108. https://doi.org/10.1016/j.jweia.2014.09.002.
  11. Matsumoto, M., Shirato, H. and Yagi, T. (2000), "Recent topics on bridge aerodynamics", Wind Struct., 3(4), 267-277. https://doi.org/10.12989/WAS.2000.3.4.267.
  12. Movaghati, S., Moghaddamjoo, A. and Tavakoli, A. (2010), "Road extraction from satellite images using particle filtering and extended Kalman filtering", IEEE Transact. Geosci. Remote Sensing, 48(7), 2807-2817. https://doi.org/10.1109/TGRS.2010.2041783.
  13. Mukherjee, A. and Sengupta, A. (2010), "Likelihood function modeling of particle filter in presence of non-stationary non-gaussian measurement noise", Signal Processing, 90(6), 1873-1885. https://doi.org/10.1016/j.sigpro.2009.12.005.
  14. Shi, J., Guo, H. and Chen, D. (2021), "Parameter identification method for lithium-ion batteries based on recursive least square with sliding window difference forgetting factor", J. Energy Storage. https://doi.org/10.1016/j.est.2021.103485.
  15. Tamura, Y. and Suganuma, S.Y. (1996), "Evaluation of amplitude-dependent damping and natural frequency of buildings during strong winds", J. Wind Eng. Ind. Aerod., 59(2-3), 115-130. https://doi.org/10.1016/0167-6105(96)00003-7.
  16. Wang, Y. and Chen, X. (2022), "Extraction of aerodynamic damping and prediction of vortex-induced vibration of bridge deck using CFD simulation of forced vibration", J. Wind Eng. Ind. Aerod., 224, 104982. https://doi.org/10.1016/j.jweia.2022.104982.
  17. Wang, Y., Chen, X. and Li, Y. (2020), "Nonlinear self-excited forces and aerodynamic damping associated with vortex-induced vibration and flutter of long span bridges", J. Wind Eng. Ind. Aerod., 204, 104207. https://doi.org/10.1016/j.jweia.2020.104207.
  18. Wu, Y. and Chen, X. (2020), "Identification of nonlinear aerodynamic damping from stochastic crosswind response of tall buildings using unscented Kalman filter technique", Eng. Struct., 220, 110791. https://doi.org/10.1016/j.engstruct.2020.110791.
  19. Zhang, J., Zhang, M., Li, Y., Qian, Y. and Huang, B. (2020), "Local wind characteristics on bridge deck of twin-box girder considering wind barriers by large-scale wind tunnel tests", Nat. Haz., 103, 751-766. https://doi.org/10.1007/s11069-020-04010-y.
  20. Zhang, M. Xu, F., Wu, T. and Zhang, Z. (2020), "Postflutter analysis of bridge decks using aerodynamic-describing functions", J. Bridge Eng., 25(8), https://doi.org/10.1061/(ASCE)BE.1943-5592.0001587.
  21. Zhao, L., Liu, S., Yan, J. and Ge, Y. (2021), "Aerodynamic modeling for streamlined box girders using nonlinear differential equations and validation in actively generated turbulence", Wind Struct., 33, 71-86. https://doi.org/10.12989/was.2021.33.1.071.
  22. Zheng, L., Zhu, J., Wang, G., Lu, D.D. and He, T. (2018), "Differential voltage analysis based state of charge estimation methods for lithium-ion batteries using extended Kalman filter and particle filter", Energy, 158, 1028-1037. https://doi.org/10.1016/j.energy.2018.06.113.
  23. Zhu, L., Qian, C., Shen, Y. and Zhu, Q. (2022), "Aerodynamic shape optimization emphasizing static stability for a super-long span cable-stayed bridge with a central-slotted box deck", Wind Struct., 35(5), 337. https://doi.org/10.12989/was.2022.35.5.337.
  24. Zhu, Y. and Shuang, M. (2020), "Influence of non-Gaussian characteristics of wind load on fatigue damage of wind turbine", Wind Struct., 31(3), 217-227. https://doi.org/10.12989/was.2020.31.3.217.