A New Damage Identification Strategy for SHM Based On FBGs and Bayesian Model Updating Method
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A New Damage Identification Strategy for SHM Based On FBGs and Bayesian Model Updating Method

Authors: Yanhui Zhang, Wenyu Yang

Abstract:

One of the difficulties of the vibration-based damage identification methods is the nonuniqueness of the results of damage identification. The different damage locations and severity may cause the identical response signal, which is even more severe for detection of the multiple damage. This paper proposes a new strategy for damage detection to avoid this nonuniqueness. This strategy firstly determines the approximates damage area based on the statistical pattern recognition method using the dynamic strain signal measured by the distributed fiber Bragg grating, and then accurately evaluates the damage information based on the Bayesian model updating method using the experimental modal data. The stochastic simulation method is then used to compute the high-dimensional integral in the Bayesian problem. Finally, an experiment of the plate structure, simulating one part of mechanical structure, is used to verify the effectiveness of this approach.

Keywords: Bayesian method, damage detection, fiber Bragg grating, structural health monitoring.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1331355

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References:


[1] Sohn H, Law KH. A Bayesian probabilistic approach for structure damage detection. Earthquake Engineering & Structural Dynamics. 1997, pp: 1259-81.
[2] Cheung SH, Beck JL. Calculation of Posterior Probabilities for Bayesian Model Class Assessment and Averaging from Posterior Samples Based on Dynamic System Data. Computer-Aided Civil and Infrastructure Engineering. 2010, pp: 304-21.
[3] Panopoulou A, Loutas T, Roulias D, Fransen S, Kostopoulos V. Dynamic fiber Bragg gratings based health monitoring system of composite aerospace structures. Acta Astronautica. 2011,In Press, Corrected Proof.
[4] Doebling SW, Farrar CR, Prime MB. A summary review of vibration-based damage identification methods. Shock and Vibration Digest. 1998, pp: 91-105.
[5] Wu ZS, Li SZ. Two-level damage detection strategy based on modal parameters from distributed dynamic macro-strain measurements. Journal of Intelligent Material Systems and Structures. 2007, pp: 667-76.
[6] Beck JL, Au SK. Bayesian updating of structural models and reliability using Markov chain Monte Carlo simulation. Journal of Engineering Mechanics-Asce. 2002, pp: 380-91.
[7] Ching JY, Chen YC. Transitional markov chain monte carlo method for Bayesian model updating, model class selection, and model averaging. Journal of Engineering Mechanics-Asce. 2007, pp: 816-32.
[8] Cheung SH, Beck JL. Bayesian Model Updating Using Hybrid Monte Carlo Simulation with Application to Structural Dynamic Models with Many Uncertain Parameters. Journal of Engineering Mechanics. 2009, pp: 243-55.
[9] Kurata M, Kim JH, Lynch JP, Law KH, Salvino LW, Asme. A Probabilistic Model Updating Algorithm For Fatigue Damage Detection In Aluminum Hull Structures. Proceedings of Proceedings of the Asme Conference on Smart Materials, Adaptive Structures and Intelligent Systems, 2010, Vol 22010.
[10] Vanik MW, Beck JL, Au SK. Bayesian probabilistic approach to structural health monitoring. Journal of Engineering Mechanics-Asce. 2000, pp:738-45.