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Comparative Study on Damage Detection for Plate Structures Using Chaotic-TLBO with Multiple Objective Functions | ||
| Journal of Rehabilitation in Civil Engineering | ||
| مقاله 6، دوره 14، شماره 2 - شماره پیاپی 42، مرداد 2026 اصل مقاله (1.89 M) | ||
| نوع مقاله: Regular Paper | ||
| شناسه دیجیتال (DOI): 10.22075/jrce.2025.2169 | ||
| نویسندگان | ||
| Ali Abedi1؛ Ali Shabani Rad1؛ Gholamreza Ghodrati Amiri* 2 | ||
| 1School of Civil Engineering, Iran University of Science and Technology, HengamStreet, Narmak, Tehran, 6765-163, Tehran, Iran | ||
| 2Natural Disasters Prevention Research Center, School of Civil Engineering, Iran University of Science and Technology, HengamStreet, Narmak, Tehran, 6765-163, Tehran, Iran | ||
| تاریخ دریافت: 07 مهر 1403، تاریخ بازنگری: 18 فروردین 1404، تاریخ پذیرش: 20 خرداد 1404 | ||
| چکیده | ||
| Structural Health Monitoring (SHM) has a crucial role in maintaining the safety and longevity of critical structures, such as buildings, bridges, and aerospace components. Early detection of structural damage, allows for timely intervention, reducing costs and preventing catastrophic failures. This study introduces an innovative approach for damage detection in plate structures by enhancing the Teaching-Learning-Based Optimization (TLBO) algorithm through the integration of chaotic maps. The proposed method, termed Chaotic Teaching-Learning-Based Optimization (CTLBO), leverages the dynamic properties of chaotic maps to improve the algorithm's performance and robustness. The proposed method utilizes modal data to solve an inverse optimization problem, aiming to enhance the accuracy of damage detection. Two benchmark plate structures namely an L-plate with dual clamps and a Rectangular plate with a quarter-circle cutout, are analyzed under noisy and noise-free conditions. Four objective functions, formulated based on modal frequencies and mode shapes, are utilized to quantify the error in damage localization and severity estimation. The effectiveness of the CTLBO algorithm is evaluated against the standard TLBO algorithm. Results demonstrate that CTLBO outperforms TLBO, particularly in noisy environments, achieving near-zero error and offering superior robustness in identifying damage locations and intensities. The findings suggest that the integration of chaotic maps improves the convergence speed and reliability of the TLBO algorithm, making it a promising tool for real-world SHM applications. | ||
تازه های تحقیق | ||
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| کلیدواژهها | ||
| Damage detection؛ Plate structure؛ Chaotic maps؛ Modal data؛ Chaotic-TLBO | ||
| مراجع | ||
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[1] Abdeljaber O, Avci O, Kiranyaz S, Gabbouj M, Inman DJ. Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks. J Sound Vib 2017;388:154–70.
[2] Avci O, Abdeljaber O, Kiranyaz S, Hussein M, Gabbouj M, Inman DJ. A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications. Mech Syst Signal Process 2021;147:107077. https://doi.org/10.1016/j.ymssp.2020.107077.
[3] Farrar CR, Worden K. An Introduction to Structural Health Monitoring, 2010, p. 1–17. https://doi.org/10.1007/978-3-7091-0399-9_1.
[4] Sohn H, Farrar CR, Hemez F, Czarnecki J. A Review of structural health. LibraryLanlGov 2001:1–7.
[5] Soleymani A, Jahangir H, Nehdi ML. Damage detection and monitoring in heritage masonry structures: Systematic review. Constr Build Mater 2023;397:132402. https://doi.org/10.1016/j.conbuildmat.2023.132402.
[6] Kaveh A, Hoseini Vaez SR, Hosseini P. Enhanced vibrating particles system algorithm for damage identification of truss structures. Sci Iran 2019;26:246–56.
[7] Xia Y, Hao H. Statistical damage identification of structures with frequency changes. J Sound Vib 2003;263:853–70. https://doi.org/10.1016/S0022-460X(02)01077-5.
[8] Daneshvar MH, Saffarian M, Jahangir H, Sarmadi H. Damage identification of structural systems by modal strain energy and an optimization-based iterative regularization method. Eng Comput 2023;39:2067–87. https://doi.org/10.1007/s00366-021-01567-5.
[9] Soleymani A, Jahangir H, Rashidi M, Mojtahedi FF, Bahrami M, Javanmardi A. Damage Identification in Reinforced Concrete Beams Using Wavelet Transform of Modal Excitation Responses. Buildings 2023;13:1955. https://doi.org/10.3390/buildings13081955.
[10] Hamdy O, Nawar MT. Damage Detection in Members and Connections of Plane Frame with Flexible Connections Using Residual Force Method and Whale Optimization Algorithm. Iran J Sci Technol Trans Civ Eng 2024;48:1917–31. https://doi.org/10.1007/s40996-023-01316-2.
[11] Jahangir H, Hasani H, dos Santos JVA, Lopes HM. A Comprehensive Study on the Selection of Mother Wavelets and Mode Shapes for Multiple Damage Identification. Iran J Sci Technol Trans Civ Eng 2024;48:1313–27. https://doi.org/10.1007/s40996-024-01394-w.
[12] Ghodrati Amiri G, Seyed Razzaghi SA, Bagheri A. Damage detection in plates based on pattern search and Genetic algorithms. Smart Struct Syst 2011;7:117–32. https://doi.org/10.12989/sss.2011.7.2.117.
[13] Friswell MI, Mottershead JE. Finite Element Model Updating in Structural Dynamics. vol. 38. Dordrecht: Springer Netherlands; 1995. https://doi.org/10.1007/978-94-015-8508-8.
[14] Khanahmadi M, Khalighi M. Interfacial Debonding Detection in Concrete-Filled Steel Tubular (CFST) Columns with Modal Curvature-Based Irregularity Detection Indices. Int J Struct Stab Dyn 2024;24. https://doi.org/10.1142/S0219455424501487.
[15] Kaveh A, Vaez SRH, Hosseini P, Fallah N. Detection of damage in truss structures using Simplified Dolphin Echolocation algorithm based on modal data. Smart Struct Syst 2016;18:983–1004.
[16] Nouri Y, Shariatmadar H, Shahabian F. Nonlinearity detection using new signal analysis methods for global health monitoring. Sci Iran 2022. https://doi.org/10.24200/sci.2022.58196.5610.
[17] 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, vol. 68, Elsevier; 2024, p. 107211. https://doi.org/10.1016/j.istruc.2024.107211.
[18] 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.
[19] Fakharian P, Naderpour H. Damage Severity Quantification Using Wavelet Packet Transform and Peak Picking Method. Pract Period Struct Des Constr 2022;27:4021063. https://doi.org/10.1061/(asce)sc.1943-5576.0000639.
[20] 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.
[21] Azimi M, Eslamlou AD, Pekcan G. Data-driven structural health monitoring and damage detection through deep learning: State-ofthe- art review. Sensors (Switzerland) 2020;20. https://doi.org/10.3390/s20102778.
[22] Kaveh A, Shabani Rad A. Metaheuristic-based optimal design of truss structures using algebraic force method. Structures, vol. 50, Elsevier; 2023, p. 1951–64. https://doi.org/10.1016/j.istruc.2023.02.123.
[23] Ruiz DV, Bragança CSC de, Poncetti BL, Bittencourt TN, Futai MM. Vibration-based structural damage detection strategy using FRFs and machine learning classifiers. Structures 2024;59:105753. https://doi.org/10.1016/j.istruc.2023.105753.
[24] Nouri Y, Shahabian F, Shariatmadar H, Entezami A. Structural Damage Detection in the Wooden Bridge Using the Fourier Decomposition, Time Series Modeling and Machine Learning Methods. J Soft Comput Civ Eng 2024;8:83–101. https://doi.org/10.22115/scce.2023.401971.1669.
[25] Kourehli SS. Structural Damage Detection under Short Time Load Using Cascade-Forward Network. J Rehabil Civ Eng 2024;12:32–42. https://doi.org/10.22075/jrce.2023.31320.1885.
[26] Yang M, Zhong H. Damage detection for plate-like structures using generalized curvature mode shape method. Earth Sp 2018 Eng Extrem Environ - Proc 16th Bienn Int Conf Eng Sci Constr Oper Challenging Environ 2018;6:1078–87. https://doi.org/10.1061/9780784481899.101.
[27] Hoseini Vaez SR, Fallah N. Damage Detection of Thin Plates Using GA-PSO Algorithm Based on Modal Data. Arab J Sci Eng 2017;42:1251–63. https://doi.org/10.1007/s13369-016-2398-6.
[28] Mohamadinasab M, Amiri GG, Dehcheshmeh MM. Structural Damage Detection of Symmetric and Asymmetric Strutures Using Different Objective Functions and Multiverse Optimizer. Iran Univ Sci Technol 2023;13:391–411. https://doi.org/10.22068/ijoce.2023.13.4.563.
[29] Fan W, Qiao P. A 2-D continuous wavelet transform of mode shape data for damage detection of plate structures. Int J Solids Struct 2009;46:4379–95. https://doi.org/10.1016/j.ijsolstr.2009.08.022.
[30] Xiang J, Liang M. A two-step approach to multi-damage detection for plate structures. Eng Fract Mech 2012;91:73–86. https://doi.org/10.1016/j.engfracmech.2012.04.028.
[31] Seyedpoor SM, Yahyapour R, Mofdi AA, Fallahian S. Structural Damage Identification through an Optimal Sensor Placement Approach and the Modal Strain Energy Based Index. J Rehabil Civ Eng 2024;12. https://doi.org/10.22075/jrce.2023.29823.1805.
[32] Mohamadi Dehcheshmeh M, Amiri GG, Zare Hosseinzadeh A, Torbatinejad V. Structural damage detection based on modal data using moth-flame optimization algorithm. Proc Inst Civ Eng - Struct Build 2019:1–43. https://doi.org/10.1680/jstbu.18.00121.
[33] Mueller DW. An introduction to the finite element method using MATLAB. Int J Mech Eng Educ 2005;33:260–77. https://doi.org/10.7227/IJMEE.33.3.8.
[34] Reddy JN. An Introduction to the Finite Element Method 1993.
[35] Timoshenko S. Goodier. JN, Theory of Elasticity. New York McGraw—Hil1 1970;970:279–91.
[36] Zienkiewicz OC, Taylor RL. The finite element method for solid and structural mechanics. Elsevier; 2005.
[37] 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.
[38] Bucolo M, Caponetto R, Fortuna L, Frasca M, Rizzo A. Does chaos work better than noise? IEEE Circuits Syst Mag 2002;2:4–19.
[39] Ott E, Wiesenfeld K. Chaos in Dynamical Systems . vol. 47. Cambridge university press; 1994. https://doi.org/10.1063/1.2808369.
[40] Talatahari S, Azizi M. Chaos Game Optimization: a novel metaheuristic algorithm. Artif Intell Rev 2021;54:917–1004. https://doi.org/10.1007/s10462-020-09867-w.
[41] Kaur G, Arora S. Chaotic whale optimization algorithm. J Comput Des Eng 2018;5:275–84. https://doi.org/10.1016/j.jcde.2017.12.006.
[42] Rao R V., Savsani VJ, Vakharia DP. Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems. CAD Comput Aided Des 2011;43:303–15. https://doi.org/10.1016/j.cad.2010.12.015. | ||
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