شناسایی آسیب در سازه‌های قاب خمشی با استفاده از پارامتر شکل مودی و الگوریتم‌ فراابتکاری IMRFO

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری سازه، دانشکدة مهندسی عمران، دانشگاه سمنان

2 استاد، دانشکده مهندسی عمران، دانشگاه سمنان

چکیده

این پژوهش روشی نوین مبتنی بر به‌روزرسانی مدل اجزا محدود برای شناسایی دقیق آسیب در قاب‌های خمشی ارائه می‌دهد. تابع هدف پیشنهادی با تأکید بر پارامتر شکل مودی و ترکیب آن با فرکانس‌های طبیعی، حساسیت بالایی برای شناسایی دقیق شدت و محل آسیب ایجاد می‌کند. برای حل مسئله معکوس، بهینه‌سازی این تابع هدف با استفاده از الگوریتم بهبودیافته جستجوی غذای سفره‌ماهی (IMRFO) انجام می‌گیرد که با استفاده از نگاشت آشوبناک Tent، استراتژی جستجوی دوطرفه و پرواز لوی، کاستی‌های MRFO استاندارد مانند دقت پایین همگرایی و گیر افتادن در بهینه‌های محلی را برطرف می‌کند. نگاشت Tent توزیع یکنواخت راه‌حل‌های اولیه را بهبود می‌بخشد، جستجوی دوطرفه باعث گسترش دامنه و پرواز لوی خروج از بهینه‌های محلی را تقویت می‌کند. IMRFO در سناریوهای متفاوت آسیب و تحت نویزهای مختلف با خطای کمتر از 2% در میانگین 20 اجرای مستقل، دقت و مقاومت بالایی در بهینه‌سازی تابع هدف را در مقایسه با الگوریتم‌های دیگر نشان داد. این چارچوب با تابع هدف نوآورانه مبتنی بر پارامتر شکل مودی و IMRFO، راهکاری دقیق، مقاوم و محاسباتی بهینه برای پایش سلامت سازه‌ای فراهم می‌کند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Damage Identification in Moment Frames Using Mode Shape Parameters and IMRFO Algorithm

نویسندگان [English]

  • Soheil Sabzevari 1
  • Hosein Naderpour 2
  • Majid Gholhaki 2
1 Ph.D Candidate of Structural Engineering of Semnan University, Semnan, Iran.
2 Professor, Faculty of Civil Engineering of Semnan University, Semnan, Iran
چکیده [English]

This study presents a novel finite element model updating approach for accurate damage identification in moment-resisting frames. The proposed objective function, which integrates mode shape parameters with natural frequencies, demonstrates high sensitivity in detecting both the location and severity of structural damage. To solve the associated optimization problem, an Improved Manta Ray Foraging Optimization (IMRFO) algorithm is employed, enhanced with a Tent chaotic map, bidirectional search strategy, and Lévy flight to address the limitations of the standard MRFO, such as low convergence accuracy and susceptibility to local optima. The Tent map ensures a uniform distribution of initial solutions, the bidirectional search broadens the exploration space, and Lévy flight enables escape from local optima. IMRFO achieves high accuracy and robustness in optimizing the objective function across multiple damage scenarios and noise levels, with an average error below 2% over 20 independent runs, outperforming other algorithms. This framework, combining the mode shape-based objective function with IMRFO, offers a precise, robust, and computationally efficient solution for structural health monitoring.

کلیدواژه‌ها [English]

  • Structural Health Monitoring
  • Objective Function
  • Mode Shape Parameter
  • IMRFO Optimization Algorithm
  • Model Updating

مراجع

[1] Rytter A. Vibrational based inspection of civil engineering structures.
[2] Farrar CR, Worden K. An introduction to structural health monitoring. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 2007 Feb 15; 365(1851): 303-315. doi: 10.1098/rsta.2006.1928
[3] Gulgec NS, Takáč M, Pakzad SN. Structural damage detection using convolutional neural networks. InModel Validation and Uncertainty Quantification, Volume 3: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics 2017. 2017 Jun 8; 331-337. doi: 10.1007/978-3-319-54858-6_33
[4] Gulgec NS, Takáč M, Pakzad SN. Convolutional neural network approach for robust structural damage detection and localization. Journal of Computing in Civil Engineering. 2019 May 1; 33(3): 04019005. doi: 10.1061/(ASCE)CP.1943-5487.0000820
[5] Tibaduiza Burgos DA, Gomez Vargas RC, Pedraza C, Agis D, Pozo F. Damage identification in structural health monitoring: A brief review from its implementation to the use of data-driven applications. Sensors. 2020 Jan 29; 20(3): 733. doi: 10.3390/s20030733
[6] Bhatt P. Maximum marks maximum knowledge in physics. Allied Publishers; 2010.
[7] Soleimani Nezhad S, Khademian F, Naderpour H, Kalantari SM, Fakharian P. Signal processing-based damage detection of steel braced frame subjected to consequent excitations. Innovative Infrastructure Solutions. 2024 Dec; 9(12): 454. doi: 10.1007/s41062-024-01762-5
[8] Ezzodin A, Ghodrati Amiri G, Naderpour H, Raissi Dehkordi M. A Novel Damage Detection Method of Reinforced Concrete Frames Using Signal Processing and Extracted Near‐Fault Fling‐Step Pulses. Shock and Vibration. 2022; 2022(1): 9824882. doi: 10.1155/2022/9824882
[9] Sha G, Radzieński M, Cao M, Ostachowicz W. A novel method for single and multiple damage detection in beams using relative natural frequency changes. Mechanical Systems and Signal Processing. 2019 Oct 1; 132: 335-352. doi: 10.1016/j.ymssp.2019.06.027
[10] He WY, Ren WX. Structural damage detection using a parked vehicle induced frequency variation. Engineering Structures. 2018 Sep 1; 170: 34-41. doi: 10.1016/j.engstruct.2018.05.082
[11] Allemang RJ. A correlation coefficient for modal vector analysis. InProc. of the 1st IMAC 1982; 110-116.
[12] Ewins DJ. Modal ¹esting: ¹heory and Practice. Somerset, England: Research Studies Press Ltd. 1984.
[13] Khatir A, Tehami M, Khatir S, Abdel Wahab M. Multiple damage detection and localization in beam-like and complex structures using co-ordinate modal assurance criterion combined with firefly and genetic algorithms. Journal of Vibroengineering. 2016 Dec 31; 18(8): 5063-573. doi: 10.21595/jve.2016.17026
[14] 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. Measurement. 2023 Apr 1; 211: 112595. doi: 10.1016/j.measurement.2023.112595
[15] 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. InStructures 2024 Oct 1; 68: 107211. doi: 10.1016/j.istruc.2024.107211
[16] Mishra M, Barman SK, Maity D, Maiti DK. Ant lion optimisation algorithm for structural damage detection using vibration data. Journal of Civil Structural Health Monitoring. 2019 Feb 13; 9(1): 117-136. doi: 10.1007/s13349-018-0318-z
[17] Wei Z, Liu J, Lu Z. Structural damage detection using improved particle swarm optimization. Inverse Problems in Science and Engineering. 2018 Jun 3; 26(6): 792-810. doi: 10.1080/17415977.2017.1347168
[18] Hoseini Vaez SR, Fallah N. Damage detection of thin plates using GA-PSO algorithm based on modal data. Arabian Journal for Science and Engineering. 2017 Mar; 42(3): 1251-1263. doi: 10.1007/s13369-016-2398-6
[19] Aghajani R, Azizpour Miandoab O, Kourehli SS, Khodabandehlou A. Identification of Damage and Model Updating Using Residual Force Modal Analysis and Optimization Algorithms. Civil Infrastructure Researches. 2025 May 22;11(1):87-104. doi: 10.22091/cer.2025.11502.1584 [In Persian]
[20] Ciambella J, Pau A, Vestroni F. Modal curvature-based damage localization in weakly damaged continuous beams. Mechanical Systems and Signal Processing. 2019 Apr 15; 121: 171-182. doi: 10.1016/j.ymssp.2018.11.012
[21] Bagherkhani A, Baghlani A. Enhancing the curvature mode shape method for structural damage severity estimation by means of the distributed genetic algorithm. Engineering Optimization. 2021 Apr 3; 53(4): 683-701. doi: 10.1080/0305215X.2020.1746294
[22] Khiem NT. Mode shape curvature of multiple cracked beams and its use for crack identification in beam-like structures. Vietnam Journal of Mechanics. 2020 Jun 29; 42(2): 123-132. doi: 10.15625/0866-7136/14707
[23] Chopra AK. Dynamics of structures theory and. ISBN: 0-13-8552. 1995: 2-4.
[24] Fakharian P, Naderpour H. Damage severity quantification using wavelet packet transform and peak picking method. Practice Periodical on Structural Design and Construction. 2022 Feb 1; 27(1): 04021063. doi: 10.1061/(ASCE)SC.1943-5576.0000639
[25] Ghannadi P, Kourehli SS. Structural damage detection based on MAC flexibility and frequency using moth-flame algorithm. Struct. Eng. Mech. 2019 Jan 1; 70(6): 649-659. doi: 10.12989/sem.2019.70.6.649
[26] Wang S, Xu M. Modal strain energy-based structural damage identification: a review and comparative study. Structural Engineering International. 2019 Apr 3; 29(2): 234-248. doi: 10.1080/10168664.2018.1507607
[27] Shi Z, Law SS, Zhang L. Structural damage detection from modal strain energy change. Journal of engineering mechanics. 2000 Dec; 126(12): 1216-1223. doi: 10.1061/(ASCE)0733-9399(2000)126:12(1216)
[28] Cha YJ, Buyukozturk O. Structural damage detection using modal strain energy and hybrid multiobjective optimization. Computer‐Aided Civil and Infrastructure Engineering. 2015 May; 30(5): 347-358. doi: 10.1111/mice.12122
[29] Mohamadi Dehcheshmeh M, Ghodrati Amiri G, Zare Hosseinzadeh A, Torbatinejad V. Structural damage detection based on modal data using moth-flame optimisation algorithm. Proceedings of the Institution of Civil Engineers-Structures and Buildings. 2022 Feb; 175(2): 79-93. doi: 10.1680/jstbu.18.00121
[30] Amiri GG, Dehcheshmeh MM, Hosseinzadeh AZ. Feasibility study on model-based damage detection in shear frames using pseudo modal strain energy. Smart Structures and Systems, An International Journal. 2020 Jan; 25(1): 47-56.
[31] Chen Z, Liu Q, Pan C. Structural damage detection based on modal strain energy assurance criterion using adaptive region shrinkage assisted IGOA. InStructures. 2023 Dec 1; 58: 105458. doi: 10.1016/j.istruc.2023.105458
[32] Hao J, Zhu X, Li J. Structural damage detection for spatial frame structures with semi-rigid joints using multiple set wireless measurements. Journal of Vibration and Control. 2024 Oct 9: 10775463241290043. doi: 10.1177/10775463241290043
[33] Nguyen QT, Livaoğlu R. Modal strain energy based enhanced approaches for damage detection and severity estimation. Engineering Failure Analysis. 2023 Apr 1; 146: 107142. doi: 10.1016/j.engfailanal.2023.107142
[34] Soyoz S. Model updating techniques for structures under seismic excitation. InSeismic Structural Health Monitoring: From Theory to Successful Applications. 2019 Apr 25; 199-216. doi: 10.1007/978-3-030-13976-6_8
[35] Soyoz S, Feng MQ. Long‐term monitoring and identification of bridge structural parameters. Computer‐Aided Civil and Infrastructure Engineering. 2009 Feb; 24(2): 82-92. doi: 10.1111/j.1467-8667.2008.00572.x
[36] Bekdaş G, Nigdeli SM, Kayabekir AE, Yang XS. Optimization in civil engineering and metaheuristic algorithms: a review of state-of-the-art developments. Computational intelligence, optimization and inverse problems with applications in engineering. 2018 Sep 26: 111-137. doi: 10.1007/978-3-319-96433-1_6
[37] Bassoli E, Vincenzi L, D'Altri AM, de Miranda S, Forghieri M, Castellazzi G. Ambient vibration‐based finite element model updating of an earthquake‐damaged masonry tower. Structural Control and Health Monitoring. 2018 May; 25(5): e2150. doi: 10.1002/stc.2150
[38] Ubertini F, Cavalagli N, Kita A, Comanducci G. Assessment of a monumental masonry bell-tower after 2016 Central Italy seismic sequence by long-term SHM. Bulletin of Earthquake Engineering. 2018 Feb; 16(2): 775-801. doi: 10.1007/s10518-017-0222-7
[39] Zhao W, Zhang Z, Wang L. Manta ray foraging optimization: An effective bio-inspired optimizer for engineering applications. Engineering Applications of Artificial Intelligence. 2020 Jan 1; 87: 103300. doi: 10.1016/j.engappai.2019.103300
[40] Qu P, Yuan Q, Du F, Gao Q. An improved manta ray foraging optimization algorithm. Scientific Reports. 2024 May 5; 14(1): 10301. doi: 10.1038/s41598-024-59960-1
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