A Bayesian approach to identifying structural nonlinearity using free-decay response: Application to damage detection in composites

Journal of Sound and Vibration

Volumn 329, Issue 15, 2010, Pages 2995-3007

  Nichols, J M ^a   Link, W A ^b   Murphy, K D ^c   Olson, C C ^a  

^a NAVAL RESEARCH LABORATORY   (United States)

^b PATUXENT WILDLIFE RESEARCH CENTER   (United States)

^c UNIVERSITY OF CONNECTICUT   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADDITIVE GAUSSIAN NOISE; BAYESIAN APPROACHES; DECAY RESPONSE; INTERVAL ESTIMATE; MARKOV CHAIN MONTE CARLO METHOD; MODEL COMPOSITES; NON-LINEAR PARAMETERS; PARAMETER DISTRIBUTIONS; PARAMETER ESTIMATE; RESPONSE DATA; STRUCTURAL NONLINEARITIES; STRUCTURAL SYSTEMS;

DAMAGE DETECTION; GAUSSIAN NOISE (ELECTRONIC); MARKOV PROCESSES; MONTE CARLO METHODS;

BAYESIAN NETWORKS;

EID: 77949659173     PISSN: 0022460X     EISSN: 10958568     Source Type: Journal    
DOI: 10.1016/j.jsv.2010.02.004     Document Type: Article

References (27)

1. Kerschen G., Worden K., Vakakis A.F., and Golinval J.-C. Past, present, and future of nonlinear system identification in structural dynamics. Mechanical Systems and Signal Processing 20 (2006) 505-592
2. Mohammad K.S., Worden K., and Tomlinson G.R. Direct parameter estimation for linear and nonlinear structures. Journal of Sound and Vibration 152 (1991) 471-499
3. Worden K., Wright J.R., and Al-Hadid M.A. Experimental identification of multi-degree-of-freedom nonlinear systems using restoring force methods. International Journal of Analytical and Experimental Modal Analysis 9 (1994) 35-55
4. Feldman M. Non-linear system vibration analysis using Hilbert transform-i. Free vibration analysis method "freevib". Mechanical Systems and Signal Processing 8 2 (1994) 119-127
5. Kerschen G., Lenaerts V., and Golinval J.C. Identification of a continuous structure with a geometrical non-linearity, part i: conditioned reverse path method. Journal of Sound and Vibration 262 (2003) 889-906
6. Adams D.E., and Allemang R.J. A frequency domain method for estimating the parameters of a non-linear structural dynamic model through feedback. Mechanical Systems and Signal Processing 14 (2000) 637-656
7. Peng Z.K., Lang Z.Q., and Billings S.A. Nonlinear parameter estimation for multi-degree-of-freedom nonlinear systems using nonlinear output frequency response functions. Mechanical Systems and Signal Processing 22 7 (2008) 1582-1594
8. Nichols J.M., Marzocca P., and Milanese A. On the use of the auto-bispectral density for detecting quadratic nonlinearity in structural systems. Journal of Sound and Vibration 312 4-5 (2008) 726-735
9. Link W.A., and Barker R.J. Bayesian Inference with Ecological Examples (2010), Academic Press, San Diego, CA
10. McDonough R.N., and Whalen A.D. Detection of Signals in Noise. second ed. (1995), Academic Press, San Diego
11. Beck J.L., and Katafygiotis L.S. Updating models and their uncertainties. i: Bayesian statistical framework. Journal of Engineering Mechanics 124 4 (1998) 455-461
12. Katafygiotis L.S., and Beck J.L. Updating models and their uncertainties. ii: Model identifiability. Journal of Engineering Mechanics 124 4 (1998) 463-467
13. Beck J.L., and Yuen K.-V. Model selection using response measurements: Bayesian probabilistic approach. ASCE Journal of Engineering Mechanics 130 2 (2004) 192-203
14. Sohn H., and Law K.H. A Bayesian probabilistic approach for structure damage detection. Earthquake Engineering and Structural Dynamics 26 (1997) 1259-1281
15. Sohn H., and Law K.H. Bayesian probabilistic damage detection of a reinforced-concrete bridge column. Earthquake Engineering and Structural Dynamics 29 (2000) 1131-1152
16. Sohn H., and Law K.H. Application of load-dependent Ritz vectors to Bayesian probabilistic damage detection. Probabilistic Engineering Mechanics 15 (2000) 139-153
17. Metropolis N., Rosenbluth A.W., Rosenbluth M.N., Teller A.H., and Teller E. Equation of state calculations by fast computing machines. The Journal of Chemical Physics 21 6 (1953) 1087-1092
18. Hastings W.K. Monte carlo sampling methods using Markov chains and their applications. Biometrika 57 1 (1970) 97-109
19. Fang M., Jiang D., Gao H.J., Sun D.X., Yang R.Q., and Zhang Q. A new Bayesian automatic model selection approach for mapping quantitative trait loci under variance component model. Genetica 135 3 (2009) 429-437
20. Beck J.L., and Au S.-K. Bayesian updating of structural models and reliability using Markov chain monte carlo simulation. Journal of Engineering Mechanics-ASCE 128 4 (2002) 380-391
21. Cheung S.H., and Beck J.L. Bayesian model updating using hybrid Monte Carlo simulation with application to structural dynamic models with many uncertain parameters. Journal of Engineering Mechanics-ASCE 135 4 (2009) 243-255
22. Glaser R.E., Lee C.L., Nitao J.J., Hickling T.L., and Hanley W.G. Markov chain Monte Carlo-based method for flaw detection in beams. ASCE Journal of Engineering Mechanics 133 12 (2007) 1258-1267
23. Au S.K., Ching J., and Beck J.L. Application of subset simulation methods to reliability benchmark problems. Structural Safety 29 (2007) 183-193
24. Zhang B.-T., and Cho D.-Y. System identification using evolutionary Markov chain Monte Carlo. Journal of Systems Architecture 47 (2001) 587-599
25. Kerschen G., Golinval J.-C., and Hemez F.M. Bayesian model screening for the identification of nonlinear mechanical structures. Journal of Vibration and Acoustics 125 (2003) 389-397
26. Murphy K.D., and Nichols J.M. A low-dimensional model for delamination in composite structures: theory and experiment. International Journal of Nonlinear Mechanics 44 (2008) 13-18
27. Nichols J.M., and Murphy K.D. Modeling and detection of delamination in a composite beam: a polyspectral approach. Mechanical Systems and Signal Processing 24 2 (2010) 365-378