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http://dx.doi.org/10.12989/sss.2016.17.4.647

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)
Publication Information
Smart Structures and Systems / v.17, no.4, 2016 , pp. 647-667 More about this Journal
Abstract
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.
Keywords
dynamic displacement; two-stage Kalman estimator; multi-rate data fusion;
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Times Cited By KSCI : 4  (Citation Analysis)
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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.   DOI
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.   DOI
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.   DOI
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.   DOI
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.   DOI
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.   DOI
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.   DOI
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.   DOI
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.   DOI
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 Kalman, R.E. (1960), "A new approach to linear filtering and prediction problems", J. Basic Eng., 82(1), 35-45.   DOI
13 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.   DOI
14 Jiang, X. and Adeli, H. (2005), "Dynamic wavelet neural network for nonlinear identification of highrise buildings", Comput.-Aided Civ. Inf., 20(5), 316-330.   DOI
15 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.   DOI
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.   DOI
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.   DOI
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.   DOI
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.   DOI
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.   DOI
21 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.   DOI
22 Moore, J.B. (1973), "Discrete-time fixed-lag smoothing algorithms", Automatica, 9(2), 163-173.   DOI
23 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.   DOI
24 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.   DOI
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.   DOI
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.   DOI
27 Rauch, H.E. (1963), "Solutions to the linear smoothing problem", IEEE T. Automat Contr., 8(4), 371-372.   DOI
28 Ruiz-Sandoval, M.E. and Morales, E. (2013), "Complete decentralized displacement control algorithm", Smart Struct. Syst., 11(2), 163-183.   DOI
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.   DOI
30 Simon, D. (2006), Optimal state estimation-Kalman, $H{\infty}$, and nonlinear approaches, John Wiley & Sons Inc., Hoboken, NJ.
31 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.   DOI
32 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.   DOI
33 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.   DOI
34 Trifunac, M.D. (1971), "Zero baseline correction of strong motion accelerograms", B. Seismol. Soc. Am., 61(5), 1201-1211.
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.   DOI
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.   DOI
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.   DOI