DOI QR코드

DOI QR Code

Dynamic displacement estimation by fusing biased high-sampling rate acceleration and low-sampling rate displacement measurements using two-stage Kalman estimator

  • Kim, Kiyoung (Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology) ;
  • Choi, Jaemook (Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology) ;
  • Koo, Gunhee (Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology) ;
  • Sohn, Hoon (Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology)
  • 투고 : 2015.12.27
  • 심사 : 2016.02.20
  • 발행 : 2016.04.25

초록

In this paper, dynamic displacement is estimated with high accuracy by blending high-sampling rate acceleration data with low-sampling rate displacement measurement using a two-stage Kalman estimator. In Stage 1, the two-stage Kalman estimator first approximates dynamic displacement. Then, the estimator in Stage 2 estimates a bias with high accuracy and refines the displacement estimate from Stage 1. In the previous Kalman filter based displacement techniques, the estimation accuracy can deteriorate due to (1) the discontinuities produced when the estimate is adjusted by displacement measurement and (2) slow convergence at the beginning of estimation. To resolve these drawbacks, the previous techniques adopt smoothing techniques, which involve additional future measurements in the estimation. However, the smoothing techniques require more computational time and resources and hamper real-time estimation. The proposed technique addresses the drawbacks of the previous techniques without smoothing. The performance of the proposed technique is verified under various dynamic loading, sampling rate and noise level conditions via a series of numerical simulations and experiments. Its performance is also compared with those of the existing Kalman filter based techniques.

키워드

과제정보

연구 과제 주관 기관 : Ministry of Land, Infrastructure and Transport

참고문헌

  1. Boore, D.M. (2001), "Effect of baseline corrections on displacement and response spectra for several recordings of the 1999 Chi-Chi, Taiwan, earthquake", B. Seismol. Soc. Am., 91(5), 1199-1211. https://doi.org/10.1785/0120000703
  2. Boore, D.M., Stephens, C.D. and Joyner, W.B. (2002), "Comments on baseline correction of digital strong-motion data: examples from the 1999 Hector Mine, California, earthquake", B. Seismol. Soc. Am., 92(4), 1543-1560. https://doi.org/10.1785/0120000926
  3. Cao, L. and Schwarz, H.M. (2003), "Exponential convergence of the Kalman filter based parameter estimation algorithm", Int. J. Adapt. Control, 17(10), 763-783. https://doi.org/10.1002/acs.774
  4. Chan, W.S., Xu, Y.L., Ding, X.L. and Dai, W.J. (2006), "An integrated GPS-accelerometer data processing technique for structural deformation monitoring", J. Geodesy, 80(12), 705-719. https://doi.org/10.1007/s00190-006-0092-2
  5. Chiu, H.C. (1997), "Stable baseline correction of digital strong-motion data", B. Seismol. Soc. Am., 87(4), 932-944.
  6. Cho, S., Yun, C.B. and Sim, S.H. (2015), "Displacement estimation of bridge structures using data fusion of acceleration and strain measurement incorporating finite element model", Smart Struct. Syst., 15(3), 645-663. https://doi.org/10.12989/sss.2015.15.3.645
  7. Esposito, S., Iervolino, I., d'Onofrio, A. and Santo, A. (2014), "Simulation-based seismic risk assessment of gas distribution networks", Comput.-Aided Civ. Inf., doi: 10.1111/mice.12105.
  8. Faruqi, F.A. and Turner, K.J. (2000), "Extended Kalman filter synthesis for integrated global positioning / inertial navigation systems", Appl. Math. Comput., 115(2-3), 213-227. https://doi.org/10.1016/S0377-0427(99)00176-4
  9. Gindy, M., Vaccaro, R. Nassif, H. and Velde, J. (2008), "A state-space approach for deriving bridge displacement from acceleration", Comput.-Aided Civ. Inf., 23(4), 281-290. https://doi.org/10.1111/j.1467-8667.2007.00536.x
  10. He, W., Wu., Zhishen, Kojima, Y. and Asakura, T. (2009), Failure mechanism of deformed concrete tunnels subject to diagonally concentrated load, Comput.-Aided Civ. Inf., 24(6), 416-431. https://doi.org/10.1111/j.1467-8667.2009.00600.x
  11. Hong, S., Lee, M., Rios, J. and Speyer, J.L. (2000), "Observability analysis of GPS aided INS", Proceedings of the 13th International Technical meeting of the Satellite Division of the Institute of Navigation (ION GPS 2000), Sep. 19-22, 2000, Salt Lake City, UT.
  12. Hong, Y.H., Kim, H. and Lee, H.S. (2013), "Design of the FEM-FIR filter for displacement reconstruction using accelerations and displacements measured at different sampling rates", Mech. Syst. Signal Pr., 38(2), 460-481. https://doi.org/10.1016/j.ymssp.2013.02.007
  13. Jiang, X. and Adeli, H. (2005), "Dynamic wavelet neural network for nonlinear identification of highrise buildings", Comput.-Aided Civ. Inf., 20(5), 316-330. https://doi.org/10.1111/j.1467-8667.2005.00399.x
  14. Jo, H., Sim, S.H., Tatkowski, A., Spencer, Jr., B.F. and Nelson, M.E. (2013), "Feasibility of displacement monitoring using low-cost GPS receivers", Struct. Control Health Monit., 20(9), 1240-1254. https://doi.org/10.1002/stc.1532
  15. Kalman, R.E. (1960), "A new approach to linear filtering and prediction problems", J. Basic Eng., 82(1), 35-45. https://doi.org/10.1115/1.3662552
  16. Kim, J., Kim, K. and Sohn, H. (2013a), "Data-driven physical parameter estimation for lumped mass structures from a single point actuation test", J. Sound Vib., 332(18), 4390-4402. https://doi.org/10.1016/j.jsv.2013.03.006
  17. Kim, J., Kim, K. and Sohn, H. (2013b), "In situ measurement of structural mass, stiffness, and damping using a reaction force actuator and a laser Doppler vibrometer", Smart Mater. Struct., 22(8), 085004. https://doi.org/10.1088/0964-1726/22/8/085004
  18. Kim, J., Kim, K. and Sohn, H. (2014), "Autonomous dynamic displacement estimation from data fusion of acceleration and intermittent displacement measurements", Mech. Syst. Signal Pr., 42(1-2), 194-205. https://doi.org/10.1016/j.ymssp.2013.09.014
  19. Kim, S.W. and Kim, N.S. (2011), "Multi-point displacement response measurement of civil infrastructures using digital image processing", Procedia Eng., 14, 195-203. https://doi.org/10.1016/j.proeng.2011.07.023
  20. Li, J., Hao, H., Fan, K. and Brownjohn, J. (2014), "Development and application of a relative displacement sensor for structural health monitoring of composite bridges", Struct. Control Health Monit., DOI: 10.1002/stc.1714.
  21. Moore, J.B. (1973), "Discrete-time fixed-lag smoothing algorithms", Automatica, 9(2), 163-173. https://doi.org/10.1016/0005-1098(73)90071-X
  22. Moschas, F. and Stiros, S. (2011), "Measurement of dynamic displacements and of the modal frequencies of a short-span pedestrian bridge using GPS and an accelerometer", Eng. Struct., 33(1), 10-17. https://doi.org/10.1016/j.engstruct.2010.09.013
  23. Park, H.S., Lee, H.M., Adeli, H. and Lee, I. (2007), "A new approach for health monitoring of structures: terrestrial laser scanning", Comput.-Aided Civ. Inf., 22(1), 19-30. https://doi.org/10.1111/j.1467-8667.2006.00466.x
  24. Park, H.S., Son, S., Choi, S.W. and Kim, Y. (2013), "Wireless laser range finder system for vertical displacement monitoring of mega-trusses during construction", Sensors, 13(5), 5796-5813. https://doi.org/10.3390/s130505796
  25. Park, J.W., Sim, S.H. and Jung, H.J. (2013), "Displacement estimation using multimetric data fusion", IEEE/ASME T. Mechatronics, 18(6), 1675-1682. https://doi.org/10.1109/TMECH.2013.2275187
  26. Park, K.T., Kim, S.H., Park, H.S. and Lee, K.W. (2005), "The determination of bridge displacement using measured acceleration", Eng. Struct., 27(3), 371-378. https://doi.org/10.1016/j.engstruct.2004.10.013
  27. Rauch, H.E. (1963), "Solutions to the linear smoothing problem", IEEE T. Automat Contr., 8(4), 371-372. https://doi.org/10.1109/TAC.1963.1105600
  28. Ruiz-Sandoval, M.E. and Morales, E. (2013), "Complete decentralized displacement control algorithm", Smart Struct. Syst., 11(2), 163-183. https://doi.org/10.12989/sss.2013.11.2.163
  29. Shin, S., Lee, S.U. and Kim, N.S. (2012), "Estimation of bridge displacement responses using FBG sensors and theoretical mode shapes", Struct. Eng. Mech., 42(2), 229-245. https://doi.org/10.12989/sem.2012.42.2.229
  30. Simon, D. (2006), Optimal state estimation-Kalman, $H{\infty}$, and nonlinear approaches, John Wiley & Sons Inc., Hoboken, NJ.
  31. Smyth, A. and Wu, M. (2007), "Multi-rate Kalman filtering for the data fusion of displacement and acceleration response measurements in dynamic system monitoring", Mech. Syst. Signal Pr., 21(2), 706-723. https://doi.org/10.1016/j.ymssp.2006.03.005
  32. Tamura, Y., Matsui, M., Pagnini, L.C., Ishibashi, R. and Yoshida. A. (2002), "Measurement of wind-induced response of buildings using RTK-GPS", J. Wind Eng. Ind. Aerod., 90(12-15), 1783-1793. https://doi.org/10.1016/S0167-6105(02)00287-8
  33. Trifunac, M.D. (1971), "Zero baseline correction of strong motion accelerograms", B. Seismol. Soc. Am., 61(5), 1201-1211.
  34. Wang, N., O'Malley, C., Ellingwood, B.R. and Zureick, A.H. (2011), "Bridge rating using system reliability assessment. I: Assessment and verificiation by load testing", J. Bridge Eng., 16(6), 854-862. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000172
  35. Yang. H., Takaki, T. and Ishii, I. (2012), "Real-time multidirectional modal parameter estimation of beam-shaped objects using high-speed stereo vision", Proceedings of IEEE, Sensors, Taipei, Taiwan.
  36. Yun, X., Calusdian, J., Bachmann, E.R. and McGhee, R.B. (2012), "Estimation of human foot motion during normal walking using inertial and magnetic sensor measurements", IEEE T. Instrum. Meas., 61(7), 2059-2072. https://doi.org/10.1109/TIM.2011.2179830
  37. Zhou, C., Li, H., Li, D., Lin, Y. and Yi, T. (2013), "Online damage detection using pair cointegration method of time-varying displacement", Smart Struct. Syst., 12(3-4), 309-325. https://doi.org/10.12989/sss.2013.12.3_4.309
  38. Zhu, L. (2003), "Recovering permanent displacements from seismic records of the June 9, 1994 Bolivia deep earthquake", Geophys. Res. Lett., 30(14), doi:10.1029/2003GL017302, 14.

피인용 문헌

  1. Application of High-precision Accelerometer Made in Korea to Health Monitoring of Civil Infrastructures vol.29, pp.3, 2016, https://doi.org/10.7734/COSEIK.2016.29.3.277
  2. Development of a High Precision Displacement Measurement System by Fusing a Low Cost RTK-GPS Sensor and a Force Feedback Accelerometer for Infrastructure Monitoring vol.17, pp.12, 2017, https://doi.org/10.3390/s17122745
  3. Two Stage Kalman Filter based Dynamic Displacement Measurement System for Civil Infrastructures vol.31, pp.3, 2018, https://doi.org/10.7734/COSEIK.2018.31.3.141
  4. A sensor fault detection strategy for structural health monitoring systems vol.20, pp.1, 2016, https://doi.org/10.12989/sss.2017.20.1.043
  5. Effective Heterogeneous Data Fusion procedure via Kalman filtering vol.22, pp.5, 2018, https://doi.org/10.12989/sss.2018.22.5.631
  6. KF-Based Multiscale Response Reconstruction under Unknown Inputs with Data Fusion of Multitype Observations vol.32, pp.4, 2016, https://doi.org/10.1061/(asce)as.1943-5525.0001031
  7. Investigations on state estimation of smart structure systems vol.25, pp.1, 2020, https://doi.org/10.12989/sss.2020.25.1.037
  8. Multi-rate data fusion for dynamic displacement measurement of beam-like supertall structures using acceleration and strain sensors vol.19, pp.2, 2016, https://doi.org/10.1177/1475921719857043
  9. A two-stage Kalman filter for the identification of structural parameters with unknown loads vol.26, pp.6, 2020, https://doi.org/10.12989/sss.2020.26.6.693