Static-based early-damage detection using symbolic data analysis and unsupervised learning methods
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Hu X, Shenton H W. Damage identification based on dead load redistribution methodology. Journal of Structural Engineering, 2006, 132(8): 1254–1263
Teughels A, De Roeck G. Damage detection and parameter identification by finite element model updating. Rev Eur Génie Civ, 2005, 9(1): 109–158
Rytter A. Vibration Based Inspection of Civil Engineering Structures. Aalborg University, 1993
Doebling S W, Farrar C R, Prime M B, Shevitz D W. Damage Identification and Health Monitoring of Structural and Mechanical Systems from Changes in Their Vibration Characteristics: A Literature Review. Los Alamos, USA, 1996
Sohn H, Farrar C, Hemez F M, Shunk D D, Stinemates DW, Nadler B R. A Review of Structural Health Monitoring Literature: 1996–2001. Los Alamos, USA, 2004
Alvandi A, Crémona C. Assessment of vibration-based damage identification techniques. Journal of Sound and Vibration, 2006, 292(1–2): 179–202
Posenato D, Kripakaran P, Inaudi D, Smith I F C. Methodologies for model-free data interpretation of civil engineering structures. Computers & Structures, 2010, 88(7–8): 467–482
Nair K K, Kiremidjian A S, Law K H. Time series-based damage detection and localization algorithm with application to the ASCE benchmark structure. Journal of Sound and Vibration, 2006, 291(1–2): 349–368
Moyo P, Brownjohn J M W. Detection of anomalous structural behaviour using wavelet analysis. Mechanical Systems and Signal Processing, 2002, 16(2–3): 429–445
E. Diday and Noirhomme-Fraiture. Symbolic Data Analysis and the SODAS Software. Chicester: John Wiley and Sons, 2008, 445
Cury A, Crémona C. Assignment of structural behaviours in longterm monitoring: Application to a strengthened railway bridge. Structural Health Monitoring, 2012, 11(4): 422–441
Oh C K, Sohn H. Damage diagnosis under environmental and operational variations using unsupervised support vector machine. Journal of Sound and Vibration, 2009, 325(1–2): 224–239
Hua X G, Ni Y Q, Ko J M, Wong K Y. Modeling of temperature — frequency correlation using combined principal component analysis and support vector regression technique. Journal of Computing in Civil Engineering, 2007, 21(2): 122–135
Zhou H F, Ni Y Q, Ko J M. Constructing input to neural networks for modelling temperature-caused modal variability: Mean temperatures, effective temperatures, and principal components of temperatures. Engineering Structures, 2010, 32(6): 1747–1759
Mata J. Interpretation of concrete dam behaviour with artificial neural network and multiple linear regression models. Engineering Structures, 2011, 33(3): 903–910
Ni Y Q, Hua X G, Fan K Q, Ko J M. Correlating modal properties with temperature using long-term monitoring data and support vector machine technique. Engineering Structures, 2005, 27(12): 1762–1773
Posenato D. Model-Free Data Interpretation for Continuous Monitoring of Complex Structures. École Polytechnique Fédérale de Lausanne, 2009
Cury A. Téchniques D’Anormalité Appliquées a la Surveillance de Santé Structurale. Université Paris-Est, 2010
Yan A, Kerschen G, De Boe P, Golinval J C. Structural damage diagnosis under varying environmental conditions—Part I: A linear analysis. Mechanical Systems and Signal Processing, 2005, 19(4): 865–880
Bellino A, Fasana A, Garibaldi L, Marchesiello S Ã. PCA-based detection of damage in time-varying systems. Mechanical Systems and Signal Processing, 2010, 24(7): 2250–2260
Zhou H F, Ni Y Q, Ko J M. Structural damage alarming using autoassociative neural network technique: Exploration of environmenttolerant capacity and setup of alarming threshold. Mechanical Systems and Signal Processing, 2011, 25(5): 1508–1526
Hsu T Y, Loh C H. Damage detection accommodating nonlinear environmental effects by nonlinear principal component analysis. Structural Control and Health Monitoring, 2010, 17(3): 338–354
Mujica L, Rodellar J, Fernandez A, Guemes A. Q-statistic and T2-statistic PCA-based measures for damage assessment in structures. Structural Health Monitoring, 2011, 10(5): 539–553
da Silva S, Dias Júnior M, Lopes Junior V, Brennan M J. Structural damage detection by fuzzy clustering. Mechanical Systems and Signal Processing, 2008, 22(7): 1636–1649
Sohn H, Kim S D, Harries K. Reference-Free Damage Classification Based on Cluster Analysis. Comput Civ Infrastruct Eng, 2008, 23(5): 324–338
Cury A, Crémona C, Diday E. Application of symbolic data analysis for structural modification assessment. Engineering Structures, 2010, 32(3): 762–775
Santos J, Orcesi A D, Silveira P, Guo W. Real time assessment of rehabilitation works under operational loads. In: Proceedings of the ICDS12 — International Conference on Durable Structures: From construction to rehabilitation. 2012
Hua X G, Ni Y Q, Chen Z Q, Ko J M. Structural damage detection of cable-stayed bridges using changes in cable forces and model updating. Journal of Structural Engineering, 2009, 135(9): 1093–1106
Hu X, Shenton H W III. Damage identification based on dead load redistribution effect of measurement error. Journal of Structural Engineering, 2006, 132(8): 1264–1273
Jolliffe I T. Principal Component Analysis. 2nd ed. Aberdeen: Springer, 2002, 518
Billard L, Diday E. Symbolic Data Analysis. Chichester: John Wiley and Sons, 2006, 52(2): 321
Theodoridis S, Koutroumbas K. Pattern Recognition. 4th ed. London: Elsevier, 2009, 961
Ichino M, Yaguchi H. Generalized Minkowski metrics for mixed feature-type data analysis. IEEE Transactions on Systems, Man, and Cybernetics, 1994, 24(4): 698–708
Gowda K C, Diday E. Symbolic clustering using a new dissimilarity measure. IEEE Transactions on Systems, Man, and Cybernetics, 1991, 24(6): 567–578
Hastie T. The Elements of Statistical Learning, Data Mining, Inference and Prediction. 2nd ed. Stanford, USA: Springer, 2011, 763
Milligan G, Cooper M. An examination of procedures for determining the number of clusters in a data set. Psychometrika, 1985, 50(2): 159–179
Santos J, Silveira P. A SHM framework comprising real time data validation. In: Proceedings of IALCCE 2012-3rd International Symposium on Life Cycle Civil engineering. 2012, 2
Santos J, Silveira P, Santos L O, Calado L. Monitoring of road structures—real time acquisition and control of data. In: Proceedings of the 16th IRF World Road Meeting. Lisbon, May, 2010
Santos J, Orcesi A D, Silveira P, Pina C. Damage Detection under Environmental and Operational Loads on Large Span Bridges. In: V Congresso brasileiro de Pontes e Estruturas — Soluções Inovadores para Projeto. Execuçao e Manutençao, 2012
Caetano E, Cunha Á, Gattulli V, Lepidi M. Cable-deck dynamic interactions at the international Guadiana Bridge on-site measurements and finite element modelling. Structural Control and Health Monitoring, 2008, 15(3): 237–264
Massey F J Jr. The Kolmogorov-Smirnov test for goodness of fit. Journal of the American Statistical Association, 1951, 46(253): 68–78
Jackson J E. A User’s Guide to Principal Components. Wiley-Interscience, 1991, 43(6): 641