Sparse Bayesian learning with model reduction for probabilistic structural damage detection with limited measurements
Tài liệu tham khảo
Bernal, 2002, Load vectors for damage localization, J Eng Mech, 128, 7, 10.1061/(ASCE)0733-9399(2002)128:1(7)
Doebling, 1998, A summary review of vibration-based damage identification methods, Shock Vib digest, 30, 91, 10.1177/058310249803000201
Fan, 2011, Vibration-based damage identification methods: a review and comparative study, Struct Health Monitor, 10, 83, 10.1177/1475921710365419
Li, 2011, Fractal Dimension-Based Damage Detection Method for Beams with a Uniform Cross-Section, Comput-Aided Civ Infrastruct Eng, 26, 190, 10.1111/j.1467-8667.2010.00686.x
Moaveni, B., Stavridis, A., Lombaert, G., Conte, J. P., & Shing, P. B., Finite-element model updating for assessment of progressive damage in a 3-story infilled RC frame. J Struct Eng. 139(10) (2012), 1665-1674.
Zhou, 2011, Eliminating temperature effect in vibration-based structural damage detection, J Eng Mech, 137, 785, 10.1061/(ASCE)EM.1943-7889.0000273
Asadollahi, P., Li, J., & Huang, Y., Prediction-error variance in Bayesian model updating: a comparative study. In Proc. SPIE Smart Structures/NDE 2017, 2017, Portland, OR.
Behmanesh, I., & Moaveni, B., Bayesian FE model updating in the presence of modeling errors, Model Validation and Uncertainty Quantification, Volume 3 (2014) (pp. 119-133): Springer.
Goller, 2011, Investigation of model uncertainties in Bayesian structural model updating, J Sound Vib, 330, 6122, 10.1016/j.jsv.2011.07.036
Huang, 2015, Hierarchical sparse Bayesian learning for structural health monitoring with incomplete modal data, Int J Uncertainty Quantific, 5, 10.1615/Int.J.UncertaintyQuantification.2015011808
Vanik, M. W., Beck, J., & Au, S. Bayesian probabilistic approach to structural health monitoring. J Eng Mech. 126(7) (2000), 738-745.
Arangio, 2015, Structural health monitoring of a cable-stayed bridge with Bayesian neural networks, Struct Infrastruct Eng, 11, 575, 10.1080/15732479.2014.951867
Figueiredo, 2014, A Bayesian approach based on a Markov-chain Monte Carlo method for damage detection under unknown sources of variability, Eng Struct, 80, 1, 10.1016/j.engstruct.2014.08.042
Sohn, 1997, A Bayesian probabilistic approach for structure damage detection, Earthq Eng Struct Dyn, 26, 1259, 10.1002/(SICI)1096-9845(199712)26:12<1259::AID-EQE709>3.0.CO;2-3
Yin, T., Lam, H. F., & Chow, H. M., A Bayesian probabilistic approach for crack characterization in plate structures. Computer‐Aided Civil Infrastruct Eng. 25(5) (2010), 375-386.
Yuen, 2004, Two-stage structural health monitoring approach for phase I benchmark studies, J Eng Mech, 130, 16, 10.1061/(ASCE)0733-9399(2004)130:1(16)
Yuen, K. V., Beck, J. L., & Katafygiotis, L. S. (2006). Efficient model updating and health monitoring methodology using incomplete modal data without mode matching. Struct Control Health Monitor. 13(1), 91-107.
Mao, 2020, Bayesian FEM Updating of a Long-Span Suspension Bridge Utilizing Hybrid Monte Carlo Simulation and Kriging Predictor, KSCE J Civ Eng, 24, 569, 10.1007/s12205-020-0983-4
Das, 2020, A Bayesian model updating with incomplete complex modal data, Mech Syst Sig Process, 136, 106524, 10.1016/j.ymssp.2019.106524
Hızal, 2020, A two-stage Bayesian algorithm for finite element model updating by using ambient response data from multiple measurement setups, J Sound Vib, 469, 115139, 10.1016/j.jsv.2019.115139
Xu, 2020, Sparse Bayesian Broad Learning System for Probabilistic Estimation of Prediction, IEEE Access, 8, 56267, 10.1109/ACCESS.2020.2982214
Kuok, 2021, Broad Bayesian learning (BBL) for nonparametric probabilistic modeling with optimized architecture configuration, Comput-Aided Civ Infrastruct Eng, 36, 1270, 10.1111/mice.12663
Yin, 2020, An efficient algorithm for architecture design of Bayesian neural network in structural model updating, Comput-Aided Civ Infrastruct Eng, 35, 354, 10.1111/mice.12492
He, 2020, Estimation of failure probability in braced excavation using Bayesian networks with integrated model updating, Underground Space, 5, 315, 10.1016/j.undsp.2019.07.001
Beck, 2001, Monitoring structural health using a probabilistic measure, Comput-Aided Civ Infrastruct Eng, 16, 1, 10.1111/0885-9507.00209
Huang, 2017, Bayesian system identification based on hierarchical sparse Bayesian learning and Gibbs sampling with application to structural damage assessment, Comput Methods Appl Mech Eng, 318, 382, 10.1016/j.cma.2017.01.030
Huang, 2017, Hierarchical sparse Bayesian learning for structural damage detection: Theory, computation and application, Struct Saf, 64, 37, 10.1016/j.strusafe.2016.09.001
Huang, 2020, Novel sparseness-inducing dual Kalman filter and its application to tracking time-varying spatially-sparse structural stiffness changes and inputs, Comput Methods Appl Mech Eng, 372, 113411, 10.1016/j.cma.2020.113411
Chen, 2020, Sparse Bayesian learning for structural damage identification, Mech Syst Sig Process, 140, 106689, 10.1016/j.ymssp.2020.106689
Hou, 2019, Sparse Bayesian learning for structural damage detection using expectation–maximization technique, Structural Control Health Monitor, 26, e2343, 10.1002/stc.2343
Ching, 2003
Yin, 2017, Vibration-based damage detection for structural connections using incomplete modal data by Bayesian approach and model reduction technique, Eng Struct, 132, 260, 10.1016/j.engstruct.2016.11.035
Asadollahi, 2017, Statistical analysis of modal properties of a cable-stayed bridge through long-term wireless structural health monitoring, J Bridge Eng, 22, 04017051, 10.1061/(ASCE)BE.1943-5592.0001093
Ching, J.-y., & Beck, J., Bayesian analysis of the phase II IASC–ASCE structural health monitoring experimental benchmark data. J Eng Mech. 130(10) (2004), 1233-1244.
Guyan, 1965, Reduction of stiffness and mass matrices, AIAA J, 3, 380, 10.2514/3.2874
Friswell, 1995, Model reduction using dynamic and iterated IRS techniques, J Sound Vib, 186, 311, 10.1006/jsvi.1995.0451
O’Callahan, 1989, A procedure for an improved reduced system (IRS) model
Sun, 2016, Probabilistic updating of building models using incomplete modal data, Mech Syst Sig Process, 75, 27, 10.1016/j.ymssp.2015.12.024
KIDDER, 1973, Reduction of structural frequency equations, AIAA J, 11, 892, 10.2514/3.6852
Huang, 2013, Novel sparse Bayesian learning for structural health monitoring using incomplete modal data, Computing Civ Eng, 121, 10.1061/9780784413029.016
Tipping, 2001, Sparse Bayesian learning and the relevance vector machine, J Mach Learn Res, 1, 211
Beck, J. L. and Katafygiotis, L. S., Updating models and their uncertainties. I: Bayesian statistical framework, J. Engrg. Mech., 124(4) (1998),455–461.
Bernal, 2002, Phase II of the ASCE benchmark study on SHM, 1048
Asadollahi, 2018, Bayesian Finite Element Model Updating and Assessment of Cable-Stayed Bridges Using Wireless Sensor Data, Sensors, 18, 3057, 10.3390/s18093057
Caicedo, 2003
Giraldo, 2009, Modal Identification througth Ambient Vibration: Comparative Study, J Eng Mech, 135, 759, 10.1061/(ASCE)0733-9399(2009)135:8(759)
Li, 2014, Parametric Time-domain Identification of Multiple-Input Systems Using Decoupled Output Signals, Earthq Eng Struct Dyn, 43, 1307, 10.1002/eqe.2398