References
- Doebling SW, Farrar CR, Prime MB. A summary review of vibration-based damage identification methods. Shock Vibr Digest. 1998;30(2):91–105.
- Carden EP. Vibration based condition monitoring: a review. Struct Health Monit. 2004;3(4):355–377.
- Brownjohn JMW. Structural health monitoring of civil infrastructure. Philos Trans R Soc A: Math Phys Eng Sci. 2007;365(1851):589–622.
- Fan W, Qiao P. Vibration-based damage identification methods: a review and comparative study. Struct Health Monit. 2010;9(3):83–111.
- Kim J, Lynch JP, Lee JJ, et al. Truck-based mobile wireless sensor networks for the experimental observation of vehicle-bridge interaction. Smart Mater Struct. 2011;20(6):1645–1648.
- Zhu XQ, Law SS. Recent developments in inverse problems of vehicle–bridge interaction dynamics. J Civil Struct Health Monit. 2016;6(1):107–128.
- Yang YB, Yang JP. State-of-the-art review on modal identification and damage detection of bridges by moving test vehicles. Int J Struct Stab Dyn. 2017;6:1850025.
- Zhu XQ, Law SS. Wavelet-based crack identification of bridge beam from operational deflection time history. Int J Solids Struct. 2006;43(43):2299–2317.
- Hester D, González A. A wavelet-based damage detection algorithm based on bridge acceleration response to a vehicle. Mech Syst Signal Process. 2012;28(2):145–166.
- Sun Z, Nagayama T, Su D, et al. A damage detection algorithm utilizing dynamic displacement of bridge under moving vehicle. Shock Vib. 2016;6:1–9.
- Li J, Law SS. Damage identification of a target substructure with moving load excitation. Mech Syst Signal Process. 2012;30(7):78–90.
- He X, Kawatani M, Hayashikawa T, et al. A bridge damage detection approach using Train-bridge interaction analysis and GA optimization. Procedia Eng. 2011;14(2259):769–776.
- Zhan JW, Xia H, Chen SY, et al. Structural damage identification for railway bridges based on train-induced bridge responses and sensitivity analysis. J Sound Vib. 2011;330(4):757–770.
- Roveri N, Carcaterra A. Damage detection in structures under traveling loads by Hilbert–huang transform. Mech Syst Signal Process. 2012;28:128–144.
- Meredith J, Gonzalez A, Hester D. Empirical mode decomposition of the acceleration response of a prismatic beam subject to a moving load to identify multiple damage locations. Shock Vib. 2012;19(5):845–856.
- Lu ZR, Liu JK. Identification of both structural damages in bridge deck and vehicular parameters using measured dynamic responses. Comput Struct. 2011;89(13):1397–1405.
- Zhang X, Sun G, Sun Y, et al. Simultaneous identification of vehicular parameters and structural damages in bridge. Wuhan Univ J Nat Sci. 2018;23(1):84–92.
- Li J, Law SS, Hao H. Improved damage identification in bridge structures subject to moving loads: numerical and experimental studies. Int J Mech Sci. 2013;74(3):99–111.
- Feng D, Feng MQ, et al. Model updating of railway bridge using in situ dynamic displacement measurement under trainloads. J Bridge Eng. 2015;20(12):04015019.
- Liu X, Escamilla-Ambrosio PJ, Lieven NAJ. Extended Kalman filtering for the detection of damage in linear mechanical structures. J Sound Vib. 2009;325(4-5):1023–1046.
- Ding Y, Zhao BY, Wu B, et al. A condition assessment method for time-variant structures with incomplete measurements. Mech Syst Signal Process. 2015;58:228–244.
- Lai Z, Lei Y, Zhu S, et al. Moving-window extended Kalman filter for structural damage detection with unknown process and measurement noises. Measurement. 2016;88:428–440.
- Liu L, Su Y, Zhu J, et al. Data fusion based EKF-UI for real-time simultaneous identification of structural systems and unknown external inputs. Measurement. 2016;88:456–467.
- Yang JN, Lin S, Huang H, et al. An adaptive extended Kalman filter for structural damage identification. Struct Control Health Monit. 2006;13(4):849–867.
- Yang JN, Pan S, Huang H. An adaptive extended Kalman filter for structural damage identifications II: unknown inputs. Struct Control Health Monit. 2007;14(3):497–521.
- Zhou Q, Liu Y, Wang X, et al. Structural damage detection technique with limited input and output measurement signals. Mech Syst Signal Process. 2012;26(5):229–243.
- Lei Y, Wu Y, Li T. Identification of non-linear structural parameters under limited input and output measurements. Int J Non Linear Mech. 2012;47(10):1141–1146.
- Weber B, Paultre P, Proulx J. Consistent regularization of nonlinear model updating for damage identification. Mech Syst Signal Process. 2009;23(6):1965–1985.
- Rucevskis S, Sumbatyan MA, Akishin P, et al. Tikhonov’s regularization approach in mode shape curvature analysis applied to damage detection. Mech Res Commun. 2015;65:9–16.
- Zhang C, Huang J-Z, Song G-Q, et al. Detection of structural damage via free vibration responses by extended Kalman filter with Tikhonov regularization scheme. Struct Monit Maint, Int J. 2016;3(2):115–127.
- Park HW, Man WP, Ahn BK, et al. 1-Norm-based regularization scheme for system identification of structures with discontinuous system parameters. Int J Numer Methods Eng. 2007;69(3):504–523.
- Zhang CD, Xu YL. Comparative studies on damage identification with Tikhonov regularization and sparse regularization. Struct Control Health Monit. 2016;23(3):560–579.
- Zhou S, Bao Y, Li H, et al. Structural damage identification based on substructure sensitivity and l1sparse regularization. //SPIE Smart Structures and Materials+ Nondestructive Evaluation and Health Monitoring. International Society for Optics and Photonics, 2013; 8692:86923N1-86923N8.
- Mascarenas D, Cattaneo A, Theiler J, et al. Compressed sensing techniques for detecting damage in structures. Struct Health Monit. 2013;12(4):325–338.
- Yang Y, Nagarajaiah S. Output-only modal identification by compressed sensing: Non-uniform low-rate random sampling. Mech Syst Signal Process. 2015;56-57:15–34.
- Grewal MS, Andrews AP. Kalman filtering: theory and practice using MATLAB. 2nd ed. New York: John Wiley and Sons, Inc.; 2001.
- James G M, Peter R, Lv J. DASSO: connections between the Dantzig selector and lasso. J R Stat Soc. 2009;71(1):127–142.
- Carmi A, Gurfil P, Kanevsky D. Methods for sparse signal Recovery using Kalman filtering with embedded pseudo-measurement norms and quasi-norms. IEEE Trans Signal Process. 2010;58(4):2405–2409.
- Lawson CL, Hanson RJ. Solving least squares problems. Englewood Cliffs, NJ: Prentice-Hall; 1974.
- Feng D, Sun H, Feng MQ. Simultaneous identification of bridge structural parameters and vehicle loads. Comput Struct. 2015;157:76–88.
- Karoumi R. Response of cable-stayed and suspension bridges to moving vehicles: analysis methods and practical modeling techniques. Stockholm: KTH Royal Institute of Technology; 1998.
- Jinguang C, Lili MA. Error performance analysis of Kalman filtering algorithm for Non-Gaussian system. Electron Optics Control. 2010;17(9):30–33. (in Chinese).
- International Organization for Standardization (ISO). Mechanical vibration-road surface profiles-reporting of measured data. ISO 8068: 1995 (E), ISO.Geneva; 1995.
- Honda H, Kajikawa Y, Kobori T. Spectra of road surface roughness on bridges. J Struct Div. 1982;108(9):1956–1966.