Nonparametric structural damage detection algorithm for ambient vibration response: Utilizing artificial neural networks and self-organizing maps

Journal of Architectural Engineering

Volumn 22, Issue 2, 2016, Pages

  Abdeljaber, Osama ^a   Avci, Onur ^a  

^a Qatar University   (Qatar)

Author keywords

Artificial neural network algorithm; Nonparametric damage detection; Self organizing maps; Structural damage detection; Structural health monitoring

Indexed keywords

CONFORMAL MAPPING; FINITE ELEMENT METHOD; PATTERN RECOGNITION; SELF ORGANIZING MAPS; SIGNAL DETECTION; STRUCTURAL ANALYSIS; STRUCTURAL HEALTH MONITORING;

AMBIENT VIBRATIONS; ARTIFICIAL NEURAL NETWORK ALGORITHM; HOT ROLLED STEELS; NON-PARAMETRIC; SENSITIVITY STUDIES; STRUCTURAL DAMAGE DETECTION; STRUCTURAL DAMAGES; VIBRATION-BASED DAMAGE DETECTION;

DAMAGE DETECTION;

EID: 84970006585     PISSN: 10760431     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)AE.1943-5568.0000205     Document Type: Article

References (30)

1. Abaqus/CAE 6.12-1 [Computer software]. Dassault Systèmes, Providence, RI.
2. Arangio, S., and Beck, J. L. (2012). "Bayesian neural networks for bridge integrity assessment." Struct. Control Health Monit., 19(1), 3-21.
3. Arredondo, M. A. T., et al. (2014). "A pattern recognition approach for damage detection and temperature compensation in acousto-ultrasonics." EWSHM-7th European Workshop on Structural Health Monitoring, IFFSTTAR, Inria, Univ. de Nantes, Nantes, France.
4. Avci, O., and Abdeljaber, O. (2015). "Self-organizing maps for structural damage detection: A novel unsupervised vibration-based algorithm." J. Perform. Constr. Facil., 10.1061/(ASCE)CF.1943-5509.0000801, 04015043.
5. Bani-Hani., K. (1999). "Analytical and experimental study of nonlinear structural control using neural networks." Ph.D. thesis, Univ. of Illinois at Urbana-Champaign, Champaign, IL.
6. Bani-Hani, K., Ghaboussi, J., and Schneider, S. P. (1999). "Experimental study of identification and control of structures using neural network. Part 1: Identification." Earthquake Eng. Struct. Dyn., 28(9), 995-1018.
7. Bernal, D., Dyke, S. J., Lam, H.-F., and Beck, J. L. (2002). "Phase II of the ASCE benchmark study on structural health monitoring." 15th ASCE Engineering Mechanics Conf., Columbia Univ., New York.
8. Buethe, I., Kraemer, P., and Fritzen, C. P. (2012). "Applications of self-organizing maps in structural health monitoring." Key Eng. Mater., 518, 37-46.
9. Çatbaş, F. N., Kijewski-Correa, T., and Aktan, A. E. (2013). Structural identification of constructed systems. ASCE, Reston, VA.
10. Chang, C. C., Chang, T. Y. P., Xu, Y. G., and Wang, M. L. (2000). "Structural damage detection using an iterative neural network." J. Intell. Mater. Syst. Struct., 11(1), 32-42.
11. Elshafey, A. A., Haddara, M. R., and Marzouk, H. (2010). "Damage detection in offshore structures using neural networks." Mar. Struct., 23(1), 131-145.
12. Ettouney, M. M., and Alampalli, S. (2011). Infrastructure health in civil engineering: Theory and components, Vol. 1, CRC Press, Boca Raton, FL.
13. Fang, X., Luo, H., and Tang, J. (2005). "Structural damage detection using neural network with learning rate improvement." Comput. Struct., 83(25), 2150-2161.
14. Gul, M., and Catbas, F. N. (2008). "Ambient vibration data analysis for structural identification and global condition assessment." J. Eng. Mech., 10.1061/(ASCE)0733-9399(2008)134:8(650), 650-662.
15. Gul, M., and Catbas, F. N. (2010). "Damage assessment with ambient vibration data using a novel time series analysis methodology." J. Struct. Eng., 137(12), 1518-1526.
16. Jiang, S. F., Zhang, C. M., and Yao, J. (2011). "Eigen-level data fusion model by integrating rough set and probabilistic neural network for structural damage detection." Adv. Struct. Eng., 14(2), 333-350.
17. Kao, C. Y., and Hung, S. L. (2003). "Detection of structural damage via free vibration responses generated by approximating artificial neural networks." Comput. Struct., 81(28), 2631-2644.
18. Kohonen, T. (2001). Self-organizing maps, Vol. 30, Springer Science & Business Media, Berlin.
19. Lee, J., and Kim, S. (2007). "Structural damage detection in the frequency domain using neural networks." J. Intell. Mater. Syst. Struct., 18(8),785-792.
20. Lee, J. J., Lee, J. W., Yi, J. H., Yun, C. B., and Jung, H. Y. (2005). "Neural networks-based damage detection for bridges considering errors in baseline finite element models." J. Sound Vib., 280(3), 555-578.
21. Lopes, V., Park, G., Cudney, H. H., and Inman, D. J. (2000). "Impedance-based structural health monitoring with artificial neural networks." J. Intell. Mater. Syst. Struct., 11(3), 206-214.
22. Mansouri, M., Avci, O., Nounou, H., and Nounou, M. (2015a). "A comparative assessment of nonlinear state estimation methods for structural health monitoring." Proc., IMAC XXXIII Conf. and Exposition on Structural Dynamics, Springer International Publishing, Cham, Switzerland.
23. Mansouri, M., Avci, O., Nounou, H., and Nounou, M. (2015b). "Iterated square root unscented kalman filter for nonlinear states and parameters estimation: Three DOF damped system." J. Civ. Struct. Health Monit., 5(4), 493-508.
24. MATLAB 8.1.0.604 SPACE [Computer software]. MathWorks, Inc., Natick, MA.
25. Nazarko, P., and Ziemiański, L. (2011). "Application of artificial neural networks in the damage identification of structural elements." Comput. Assisted Mech. Eng. Sci., 18(3), 175-189.
26. Ng, C. T. (2014). "Application of Bayesian-designed artificial neural networks in Phase II structural health monitoring benchmark studies." Aust. J. Struct. Eng., 15(1), 27-36.
27. Pawar, P. M., Reddy, K. V., and Ganguli, R. (2007). "Damage detection in beams using spatial Fourier analysis and neural networks." J. Intell. Mater. Syst. Struct., 18(4), 347-359.
28. Tibaduiza, D. A., Mujica, L. E., and Rodellar, J. (2013). "Damage classification in structural health monitoring using principal component analysis and self-organizing maps." Struct. Control Health Monit., 20(10), 1303-1316.
29. Yan, L., Elgamal, A., and Cottrell, G. W. (2011). "Substructure vibration NARX neural network approach for statistical damage inference." J. Eng. Mech., 139(6), 737-747.
30. Yeung, W. T., and Smith, J. W. (2005). "Damage detection in bridges using neural networks for pattern recognition of vibration signatures." Eng. Struct., 27(5), 685-698.