Abstract
Destruction of dams often has extreme financial consequences and sometimes results in fatalities. Therefore, structural health monitoring is a crucial issue. In this article, the renowned Pine Flat dam has been chosen for the finite element modeling. The main objective is damage detection based on behavior evaluation of intact and damaged dams when an earthquake is applied. Three well-known earthquake records including El Centro, Northridge, and Loma Prieta, respectively, with low, middle, and high frequencies are considered in this study. At the data generation stage, the damage is induced in the dam neck and heel through elasticity modulus reduction, and then any of the aforementioned earthquakes are applied to it. In addition, for more accommodation with practical situations, the observations are contaminated with random noise to cover an amount of uncertainty due to some realistic factors. Following that, the acceleration values of different nodes of both intact and damaged structures are saved in two data vectors. Using various methods, such as discrete-time Fourier transform (DTFT), wavelet, and Wiener transforms, the differences between intact and damaged data are investigated. To provide a quantitative and precise analysis of the efficiency of each method in terms of destruction detection, the standard deviation of variations is employed. The results demonstrate that the wavelet transform outperforms other algorithms. Moreover, it is shown that wavelet transform represents the best robustness regarding noise variance in recorded observations.
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References
Abbate, A., Koay, J., Frankel, J., Schroeder, S. C., & Das, P. (1997). Signal detection and noise suppression using a wavelet transform signal processor: application to ultrasonic flaw detection. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 44(1), 14–26.
Adams, D., & Farrar, Ch. (2002). Classifying linear and nonlinear structural damage using frequency domain ARX models. Structural. Heal. Monitoring, 1(2), 185–201. https://doi.org/10.1177/1475921702001002005
Addison, P. S. (2017). The illustrated wavelet transform handbook: introductory theory and applications in science. Medicine and Finance, CRC Press.
Ali, K., & Maniat, M. (2015). Damage detection based on MCSS and PSO using modal data. Smart Structures and Systems, Techno, No., 5(15), 1253–1270.
Ali, K., Armin, D., Rahmani, P., & Soleimani, P. (2022). Optimal sensor placement in large-scale dome trusses via Q-learning-based water strider algorithm. Structural Control, and Health Monitoring, First Published,. https://doi.org/10.1002/stc.2949
Bayraktar, A. (2010). Türker, Temel, Akköse, Mehmet, Ateş, Şevket: The effect of reservoir length on seismic performance of gravity dams to near- and far-fault ground motions. Natural Hazards, 2(52), 257–275.
Calayir, Y., & Karaton, M. (2005). A Continuum damage concrete model for earthquake analysis of concrete gravity dam-reservoir systems. Soil Dynamics and Earthquake Engineering, 25, 857–869. https://doi.org/10.1016/j.soildyn.2005.05.003
Chang Peter, C., & Liu, S. (2003). Chi, Recent research in nondestructive evaluation of civil infrastructures. Journal of Materials in Civil Engineering, 15(3), 298–304. https://doi.org/10.1061/(ASCE)0899-1561(2003)15:3(298)
Chavez J and Fenves G (1994), A computer program for the earthquake analysis of concrete gravity dams including base sliding, report no: UCB/SEMM-1994/02.
Chavez J and Fenves G (1995), earthquake analysis, and the response of concrete gravity dams including base sliding, report number: UCB/SEMN-93/07.
Chopra A.K. (1980), earthquake responses of concrete gravity dams including hydrodynamic and foundation interaction effects, report number: UCB/EERC-80/01.
Chopra, A. K. (2012). Earthquake analysis of concrete dams: factors to be considered. Journal of Structural Engineering, 138(2), 205–214. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000431
Clarkson, Peter M: Optimal and Adaptive Signal Processing, Routledge, 2017.
Daubechies, I. (1990). The wavelet transforms, time-frequency localization, and signal analysis. IEEE Transactions on Information Theory, 36(5), 961–1005.
Esmaielzadeh, S., Ahmadi, H., & Hoseini, S. A. (2018). Damage detection in concrete gravity dams using signal processing algorithms based on earthquake vibrations. Journal of Vibroengineering, 21(8), 2196–2215. https://doi.org/10.21595/jve.2019.20202
Fan, J. (2018). Local Polynomial Modelling and Its Applications: Monographs on Statistics and Applied Probability. Routledge.
Fenves G and. Chopra A.K. (1984), A computer program for earthquake analysis of concrete gravity dams, report number: UBC/EERC-84/11.
Fenves G and Chopra A.K. (1986), simplified analysis for earthquake resistance design of concrete gravity dams, report number: UCB/EERC-85/10.
Giacomo, B. (2016). Landi, Luca, Diotallevi, Pier Paolo: On the output-only vibration-based damage detection of frame structures. Structural Health Monitoring, Damage Detection and Mechatronics, 7, 23–33. https://doi.org/10.1007/978-3-319-29956-3_3
Kaveh, A., & Dadras, A. (2017). Structural damage identification using enhanced thermal exchange optimization algorithm. Engineering Optimization, 50(3), 430451.
Kaveh, A., & Dadras, A. (2019). An efficient two-stage method for optimal sensor placement using graph-theoretical partitioning and evolutionary algorithms. Structural Control and Health Monitoring, 4(26), e2325.
Kaveh A., P. Rahmani and A Dadras, (2021) Guided water strider algorithm for structural damage detection using incomplete modal data, Iranian Journal of Science and Technology, Accepted for publication.
Kong, Xuan, Cai, Chun-Sheng, Hu, Jiexuan: The state-of-the-art on the framework of vibration-based structural damage identification for decision making. Applied Sciences, 5 (2017) 7, pp. 497-528,https://doi.org/10.3390/app7050497
Kourehli, S. S. (2018). Structural damage identification based on expanded mode shapes using extreme learning machine. Sharif Journal of Civil Engineering, 33(2), 91–98.
Lin, C. (2016). Ambient modal identification using non-stationary. Archive of Applied Mechanics, 86(8), 1449–1464.
Liu, M., & Gorman, D. G. (1995). Formulation of Rayleigh damping and its extensions. Computers and Structures., 57(2), 277–285. https://doi.org/10.1016/0045-7949(94)00611-6
Musafere, F., Sadhu, A., & Liu, K. (2016). Time-varying system identification using a hybrid blind source separation method. Structural Health Monitoring, Damage Detection and Mechatronics, 7, 99–104. https://doi.org/10.1007/978-3-319-29956-3_11
Oppenheim, Alan V. (1981): Digital Signal Processing, Massachusetts Institute of Technology Cambridge.
Pirboudaghi, Sajjad, Tarinejad, Reza, Alami, Mohammad Taghi (2018) Damage detection based on system identification of concrete dams using an extended finite element–wavelet transform coupled procedure, Journal of Vibration and Control https://doi.org/10.1177/1077546317722428.
Strang, Gilbert, Borre, Kai: Linear Algebra, Geodesy, and GPS, Siam, 1997.
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Esmaielzadeh, S., Mahmoodi, M.J. & Abad, M.J.S. Application of signal processing techniques in structural health monitoring of concrete gravity dams. Asian J Civ Eng 24, 2049–2063 (2023). https://doi.org/10.1007/s42107-023-00624-2
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DOI: https://doi.org/10.1007/s42107-023-00624-2