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Bridge Deck Modal Parameters Identification Using Traffic Loads | ||
| Journal of Rehabilitation in Civil Engineering | ||
| مقاله 24، دوره 13، شماره 3 - شماره پیاپی 39، آبان 2025، صفحه 215-230 اصل مقاله (914.4 K) | ||
| نوع مقاله: Regular Paper | ||
| شناسه دیجیتال (DOI): 10.22075/jrce.2025.34969.2157 | ||
| نویسندگان | ||
| Meisam Talebi* 1؛ Zahra Tabrizian2؛ Gholamreza Ghodrati Amiri3 | ||
| 1Ph.D. Candidate, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran | ||
| 2Postdoctoral Fellow, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran | ||
| 3Professor, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran | ||
| تاریخ دریافت: 16 مرداد 1403، تاریخ بازنگری: 25 آذر 1403، تاریخ پذیرش: 17 دی 1403 | ||
| چکیده | ||
| Structural Health Monitoring (SHM) has gained significant importance in recent decades, with various methods developed to detect structural damage. Many non-destructive damage detection techniques are based on vibration response analysis, where changes in modal parameters provide insights into the condition of the structure. For long-term monitoring, utilizing operational loads as the source of vibration is more practical. This paper presents a methodology that processes the forced vibration response of a bridge deck subjected to traffic loading for modal parameter identification. Specifically, the free vibration response is estimated using the Random Decrement (RD) technique combined with Empirical Mode Decomposition (EMD). The natural frequencies and mode shapes are extracted using Frequency Domain Decomposition (FDD). To validate the proposed approach, numerical models of 2D and 3D bridge decks are employed, considering various loading scenarios and the effects of load path and speed. The results indicate that the proposed method is effective for modal identification under real traffic loads, with improved accuracy observed when more complex load patterns, closer to actual conditions, are used. Additionally, the proximity of degrees of freedom to the load path enhances the precision of the results. Quantitative comparisons of modal frequencies and mode shapes validate the robustness of the methodology. | ||
تازه های تحقیق | ||
Achieved a precise estimation of natural frequencies and mode shapes with less than 5% deviation compared to simulation benchmarks.
Proposed a hybrid RD-EMD method that significantly reduces noise, ensuring reliable extraction of free vibration responses from non-stationary data.
Demonstrated insensitivity to input vibration characteristics, validating performance under diverse conditions such as wind, traffic, and seismic loads.
Utilized operational service loading (e.g., vehicular traffic) as an effective, non-invasive means for structural health monitoring. | ||
| کلیدواژهها | ||
| Modal identification؛ Traffic load؛ Frequency domain Decomposition؛ Random decrement؛ Empirical mode decomposition | ||
| مراجع | ||
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[1] Li H, Ou J. The state of the art in structural health monitoring of cable-stayed bridges. J Civ Struct Heal Monit 2016;6:43–67. https://doi.org/10.1007/s13349-015-0115-x.
[2] Sony S, Laventure S, Sadhu A. A literature review of next-generation smart sensing technology in structural health monitoring. Struct Control Heal Monit 2019;26:e2321. https://doi.org/10.1002/stc.2321.
[3] Khanahmadi M. An effective vibration-based feature extraction method for single and multiple damage localization in thin-walled plates using one-dimensional wavelet transform: A numerical and experimental study. Thin-Walled Struct 2024;204:112288. https://doi.org/10.1016/j.tws.2024.112288.
[4] Nadjafi S, Amiri GG, Hosseinzadeh AZ, Seyed Razzaghi SA. An effective approach for damage identification in beam-like structures based on modal flexibility curvature and particle swarm optimization. J Rehabil Civ Eng 2020;8:109–20. https://doi.org/10.22075/JRCE.2019.553.1081.
[5] Kourehli SS. Damage identification of structures using second-order approximation of neumann series expansion. J Rehabil Civ Eng 2020;8:81–91. https://doi.org/10.22075/JRCE.2018.13348.1242.
[6] Lale Arefi SH, Gholizad A, Seyedpoor SM. Damage detection of structures using modal strain energy with guyan reduction method. J Rehabil Civ Eng 2020;8:47–60. https://doi.org/10.22075/JRCE.2020.19803.1384.
[7] Khanahmadi M, Gholhaki M, Rezaifar O, Dezhkam B. Signal processing methodology for detection and localization of damages in columns under the effect of axial load. Meas J Int Meas Confed 2023;211:112595. https://doi.org/10.1016/j.measurement.2023.112595.
[8] Amir Abbas Fatemi, Zahra Tabrizian, Kabir aadeghi. Non-destructive static damage detection of structures using Genetic Algorithm. Eur J Environ Civ Eng 2016;3.
[9] Locke W, Redmond L, Schmid M. Evaluating OMA System Identification Techniques for Drive-by Health Monitoring on Short Span Bridges. J Bridg Eng 2022;27:1–14. https://doi.org/10.1061/(asce)be.1943-5592.0001923.
[10] Poskus E, Rodgers GW, Chase JG. Output-Only Modal Parameter Identification of Systems Subjected to Various Types of Excitation. J Eng Mech 2020;146:1–10. https://doi.org/10.1061/(asce)em.1943-7889.0001853.
[11] Pan C, Ye X, Mei L. Improved Automatic Operational Modal Analysis Method and Application to Large-Scale Bridges. J Bridg Eng 2021;26. https://doi.org/10.1061/(asce)be.1943-5592.0001756.
[12] Khanahmadi M, Mirzaei B, Dezhkam B, Rezaifar O, Gholhaki M, Amiri GG. Vibration-based health monitoring and damage detection in beam-like structures with innovative approaches based on signal processing: A numerical and experimental study. Structures 2024;68:107211. https://doi.org/10.1016/j.istruc.2024.107211.
[13] Fakharian P, Naderpour H. Damage Severity Quantification Using Wavelet Packet Transform and Peak Picking Method. Pract Period Struct Des Constr 2022;27:1–11. https://doi.org/10.1061/(asce)sc.1943-5576.0000639.
[14] Naderpour H, Fakharian P. A synthesis of peak picking method and wavelet packet transform for structural modal identification. KSCE J Civ Eng 2016;20:2859–67. https://doi.org/10.1007/s12205-016-0523-4.
[15] Khanahmadi M, Mirzaei B, Amiri GG, Gholhaki M, Rezaifar O. Vibration-based damage localization in 3D sandwich panels using an irregularity detection index (IDI) based on signal processing. Meas J Int Meas Confed 2024;224:113902. https://doi.org/10.1016/j.measurement.2023.113902.
[16] Feng ZQ, Zhao B, Hua XG, Chen ZQ. Enhanced EMD-RDT Method for Output-Only Ambient Modal Identification of Structures. J Aerosp Eng 2019;32:1–8. https://doi.org/10.1061/(asce)as.1943-5525.0001034.
[17] Huang Z, Gu M. Envelope Random Decrement Technique for Identification of Nonlinear Damping of Tall Buildings. J Struct Eng 2016;142:1–12. https://doi.org/10.1061/(asce)st.1943-541x.0001582.
[18] Song X, Ma H, Wang K. A new Developed Modal Parameter Identification Method Based on Empirical Mode Decomposition and Natural Excitation Technique. Procedia Eng 2017;199:1020–5. https://doi.org/10.1016/j.proeng.2017.09.270.
[19] Julius S. Bendat AGP. Random Data: Analysis and Measurement Procedures. John Wiley & Sons; 2010. https://doi.org/10.1002/9781118032428.
[20] Zimmerman AT, Shiraishi M, Swartz RA, Lynch JP. Automated Modal Parameter Estimation by Parallel Processing within Wireless Monitoring Systems. J Infrastruct Syst 2008;14:102–13. https://doi.org/10.1061/(ASCE)1076-0342(2008)14:1(102).
[21] Brinker R., Zhang L., Andersen P. Modal identification from Ambient Responses using FDD. Proc. Int. Modal Anal. Conf., San Antonio, Texas: 2000, p. 625–30.
[22] Zhang L, Wang T, Tamura Y. A frequency–spatial domain decomposition (FSDD) method for operational modal analysis. Mech Syst Signal Process 2010;24:1227–39. https://doi.org/10.1016/J.YMSSP.2009.10.024.
[23] Zimmerman AT, Lynch JP. Market-based frequency domain decomposition for automated mode shape estimation in wireless sensor networks. Struct Control Heal Monit 2010;17:808–24. https://doi.org/10.1002/STC.415.
[24] Batel M, Kjaer B&, Norcross G. Operational Modal Analysis – Another Way of Doing Modal Testing. Sound Vib 2002.
[25] Kordestani H, Xiang YQ, Ye XW, Jia YK. Application of the random decrement technique in damage detection under moving load. Appl Sci 2018;8. https://doi.org/10.3390/app8050753.
[26] Sabamehr A, Bagchi A, Tirca L, Panigrahi SK, Chourasia A. Effectiveness of the Random Decrement Technique in Modal Identification of Structures using Ambient Vibration Response. Struct Heal Monit 2017 2017;0:1091–8. https://doi.org/10.12783/SHM2017/13973.
[27] Chopra AK. Dynamics of Structures, Global Edition, 4th Edition . Pearson Education; 2015.
[28] He XH, Hua XG, Chen ZQ, Huang FL. EMD-based random decrement technique for modal parameter identification of an existing railway bridge. Eng Struct 2011;33:1348–56. https://doi.org/10.1016/J.ENGSTRUCT.2011.01.012.
[29] Bagheri A, Fatemi AA, Amiri GG. Simulation of earthquake records by means of empirical mode decomposition and hilbert spectral analysis. J Earthq Tsunami 2014;8. https://doi.org/10.1142/S179343111450002X.
[30] Huang NE, Wu Z. A review on Hilbert-Huang transform: Method and its applications to geophysical studies. Rev Geophys 2008;46. https://doi.org/10.1029/2007RG000228.
[31] Feldman M. Hilbert transform in vibration analysis. Mech Syst Signal Process 2011;25:735–802. https://doi.org/10.1016/J.YMSSP.2010.07.018.
[32] Pedro G, Francisco G, Carlos G, Marianela L. Damage Identification of Simply-Supported Beam Using Modal Data. 14th World Conf Earthq Eng 2008:8.
[33] Zhou Z, Wegner LD, Sparling BF. Data quality indicators for vibration-based damage detection and localization. Eng Struct 2021;230:111703. https://doi.org/10.1016/j.engstruct.2020.111703.
[34] Zhou Z, Wegner LD, Sparling BF. Vibration-Based Detection of Small-Scale Damage on a Bridge Deck. J Struct Eng 2007;133:1257–67. https://doi.org/10.1061/(ASCE)0733-9445(2007)133:9(1257).
[35] Pinkaew T, Asnachinda P. Experimental study on the identification of dynamic axle loads of moving vehicles from the bending moments of bridges. Eng Struct 2007;29:2282–93. https://doi.org/10.1016/J.ENGSTRUCT.2006.11.017.
[36] Marwala T. Finite-element-model updating using computional intelligence techniques: Applications to structural dynamics. Springer London; 2010. https://doi.org/10.1007/978-1-84996-323-7. | ||
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